@inproceedings{
 title = {On A Notion of Stochastic Zeroing Barrier Function},
 type = {inproceedings},
 year = {2021},
 id = {c7ac1b6f-f029-3237-9a00-ebbeadd696a7},
 created = {2020-11-06T23:59:00.000Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
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 starred = {false},
 authored = {true},
 confirmed = {true},
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 abstract = {This note examines the safety verification of the solution of Ito’s stochastic differential equations (SDE) using the notion of stochastic zeroing barrier function (SZBF). It is shown that an extension of the recently developed zeroing barrier function concept in deterministic systems can be derived to provide an SZBF based safety verification method for Itó’s SDE sample paths. The main tools in the proposed method include Itó’s calculus and stochastic invariance concept.},
 bibtype = {inproceedings},
 author = {Tamba, Tua A. and Hu, Bin and Nazaruddin, Yul Y.},
 booktitle = {The 2021 American Control Conference, Louisiana, New Orleans, US, May 26-28, 2021}
}

This note examines the safety verification of the solution of Ito’s stochastic differential equations (SDE) using the notion of stochastic zeroing barrier function (SZBF). It is shown that an extension of the recently developed zeroing barrier function concept in deterministic systems can be derived to provide an SZBF based safety verification method for Itó’s SDE sample paths. The main tools in the proposed method include Itó’s calculus and stochastic invariance concept.

@article{
 title = {Stochastic stability analysis for Vehicular Networked Systems with State-dependent bursty fading channels: A self-triggered approach},
 type = {article},
 year = {2021},
 keywords = {Networked control systems,Self-triggered control,State-dependent fading channel,Stochastic stability},
 volume = {123},
 month = {1},
 id = {8567cdff-ad6a-319a-a7b0-8e062f4455b7},
 created = {2021-02-27T22:30:52.288Z},
 file_attached = {false},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Vehicular Networked Systems (VNS) are mobile ad hoc networks where vehicles exchange information over wireless communication networks to ensure safe and efficient operation. It is, however, challenging to ensure system safety and efficiency as the wireless channels in VNS are often subject to state-dependent deep fades where the data rate suffers a severe drop and changes as a function of vehicle states. Such couplings between vehicle states and channel states in VNS thereby invalidate the use of separation principle to design event-based control strategies. By adopting a state-dependent fading channel model, this paper presents a novel self-triggered scheme under which the VNS ensures efficient use of communication bandwidth while preserving stochastic stability. Under the proposed self-triggered scheme, this paper presents a novel source coding scheme that tracks vehicle's states with performance guarantee in the presence of state-dependent fading channels. The efficacy and advantages of the proposed scheme over other event-based strategies are verified by a leader–follower example.},
 bibtype = {article},
 author = {Hu, Bin},
 doi = {10.1016/j.automatica.2020.109352},
 journal = {Automatica}
}

Vehicular Networked Systems (VNS) are mobile ad hoc networks where vehicles exchange information over wireless communication networks to ensure safe and efficient operation. It is, however, challenging to ensure system safety and efficiency as the wireless channels in VNS are often subject to state-dependent deep fades where the data rate suffers a severe drop and changes as a function of vehicle states. Such couplings between vehicle states and channel states in VNS thereby invalidate the use of separation principle to design event-based control strategies. By adopting a state-dependent fading channel model, this paper presents a novel self-triggered scheme under which the VNS ensures efficient use of communication bandwidth while preserving stochastic stability. Under the proposed self-triggered scheme, this paper presents a novel source coding scheme that tracks vehicle's states with performance guarantee in the presence of state-dependent fading channels. The efficacy and advantages of the proposed scheme over other event-based strategies are verified by a leader–follower example.

@article{
 title = {Automation Error Type and Methods of Communicating Automation Reliability Affect Trust and Performance: An Empirical Study in the Cyber Domain},
 type = {article},
 year = {2021},
 pages = {1-11},
 id = {3d087a4e-3c27-35c5-850b-f46d41466806},
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 citation_key = {9353045},
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 bibtype = {article},
 author = {Chen, J and Mishler, S and Hu, B},
 doi = {10.1109/THMS.2021.3051137},
 journal = {IEEE Transactions on Human-Machine Systems}
}

@inproceedings{
 title = {Optimal Networked Control Systems with State-dependent Markov Channels},
 type = {inproceedings},
 year = {2021},
 id = {ac6a6f8f-6c76-364d-ae4c-77c42f05c17a},
 created = {2021-02-27T23:46:49.610Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-02-28T20:47:38.715Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper considers a co-design problem for indus- trial networked control systems to ensure both system stability and resources efficiency. The assurance of system stability and efficiency is challenging due to the fact that wireless com- munications in industrial environments are subject to shadow fading, and are stochastically correlated with their surround- ing environments. To address such challenges, this paper first introduces a novel state-dependent Markov channel model that explicitly captures the state-dependent features of the wireless communications by correlating model’s transition probabilities with environment states. Under the proposed channel model, sufficient conditions on maximum allowable transmission interval are presented to ensure almost sure asymptotic stability for the nonlinear networked control system. With the stability con- straints, the co-design problem is then formulated as constrained optimization problems, which can be efficiently solved by SDP programs for a two-state Markov channel. Simulation results are provided to demonstrate the efficacy of the proposed co-design scheme.},
 bibtype = {inproceedings},
 author = {Hu, Bin and Tamba, Tua A},
 booktitle = {The 2021 American Control Conference, Louisiana, New Orleans, US, May 26-28}
}

This paper considers a co-design problem for indus- trial networked control systems to ensure both system stability and resources efficiency. The assurance of system stability and efficiency is challenging due to the fact that wireless com- munications in industrial environments are subject to shadow fading, and are stochastically correlated with their surround- ing environments. To address such challenges, this paper first introduces a novel state-dependent Markov channel model that explicitly captures the state-dependent features of the wireless communications by correlating model’s transition probabilities with environment states. Under the proposed channel model, sufficient conditions on maximum allowable transmission interval are presented to ensure almost sure asymptotic stability for the nonlinear networked control system. With the stability con- straints, the co-design problem is then formulated as constrained optimization problems, which can be efficiently solved by SDP programs for a two-state Markov channel. Simulation results are provided to demonstrate the efficacy of the proposed co-design scheme.

@article{
 title = {Stochastic stability analysis for Vehicular Networked Systems with State-dependent bursty fading channels: A self-triggered approach},
 type = {article},
 year = {2021},
 keywords = {Networked control systems,Self-triggered control,State-dependent fading channel,Stochastic stability},
 pages = {109352},
 volume = {123},
 websites = {https://doi.org/10.1016/j.automatica.2020.109352},
 publisher = {Elsevier Ltd},
 id = {1a2913b5-5cca-3c2a-9b0b-026bb26977cb},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Vehicular Networked Systems (VNS) are mobile ad hoc networks where vehicles exchange information over wireless communication networks to ensure safe and efficient operation. It is, however, challenging to ensure system safety and efficiency as the wireless channels in VNS are often subject to state-dependent deep fades where the data rate suffers a severe drop and changes as a function of vehicle states. Such couplings between vehicle states and channel states in VNS thereby invalidate the use of separation principle to design event-based control strategies. By adopting a state-dependent fading channel model, this paper presents a novel self-triggered scheme under which the VNS ensures efficient use of communication bandwidth while preserving stochastic stability. Under the proposed self-triggered scheme, this paper presents a novel source coding scheme that tracks vehicle's states with performance guarantee in the presence of state-dependent fading channels. The efficacy and advantages of the proposed scheme over other event-based strategies are verified by a leader–follower example.},
 bibtype = {article},
 author = {Hu, Bin},
 doi = {10.1016/j.automatica.2020.109352},
 journal = {Automatica}
}

Vehicular Networked Systems (VNS) are mobile ad hoc networks where vehicles exchange information over wireless communication networks to ensure safe and efficient operation. It is, however, challenging to ensure system safety and efficiency as the wireless channels in VNS are often subject to state-dependent deep fades where the data rate suffers a severe drop and changes as a function of vehicle states. Such couplings between vehicle states and channel states in VNS thereby invalidate the use of separation principle to design event-based control strategies. By adopting a state-dependent fading channel model, this paper presents a novel self-triggered scheme under which the VNS ensures efficient use of communication bandwidth while preserving stochastic stability. Under the proposed self-triggered scheme, this paper presents a novel source coding scheme that tracks vehicle's states with performance guarantee in the presence of state-dependent fading channels. The efficacy and advantages of the proposed scheme over other event-based strategies are verified by a leader–follower example.

@inproceedings{
 title = {Optimal Networked Control Systems with State-dependent Markov Channels.},
 type = {inproceedings},
 year = {2021},
 id = {e51f44a8-a9eb-3825-9785-33e463291d65},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {B. Hu, T. Tamba},
 booktitle = {The 2021 American Control Conference, Louisiana, New Orleans, US, May 26-28}
}

@article{
 title = {Automation Error Type and Methods of Communicating Automation Reliability Affect Trust and Performance: An Empirical Study in the Cyber Domain},
 type = {article},
 year = {2021},
 pages = {1-11},
 id = {6c2c7ae5-657f-3eec-bea1-080e642de06e},
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 citation_key = {9353045},
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 bibtype = {article},
 author = {Chen, Jing and Mishler, Scott and Hu, Bin},
 doi = {10.1109/thms.2021.3051137},
 journal = {IEEE Transactions on Human-Machine Systems}
}

@inproceedings{
 title = {On Event-Triggered Implementation of Moving Target Defense Control},
 type = {inproceedings},
 year = {2020},
 keywords = {event-triggered,moving target defense,secure control,switched control systems},
 id = {fb0b94e1-ff09-3fb9-b3d6-81757f40ef64},
 created = {2021-02-27T22:44:32.498Z},
 file_attached = {false},
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 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Tamba, Tua A and Hu, Bin and Nazaruddin, Yul Y},
 booktitle = {2020 International Federation of Automatic Control (IFAC-V 2020), Germany, July 11-17}
}

@article{
 title = {Co-design of Optimal Transmission Power and Controller for Networked Control Systems Under State-dependent Markovian Channels},
 type = {article},
 year = {2020},
 id = {f555cc1f-9708-3328-916a-8498a72d4a59},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {hu2020co},
 source_type = {article},
 private_publication = {false},
 bibtype = {article},
 author = {Hu, Bin and Tamba, Tua A},
 journal = {arXiv preprint arXiv:2011.13980}
}

@article{
 title = {Event-Based Adaptive Power Control in Vehicular Networked Systems with State-Dependent Bursty Fading Channels},
 type = {article},
 year = {2019},
 keywords = {Vehicular networked system,adaptive power control,almost sure asymptotic stability,state-dependent fading channel},
 pages = {506-510},
 volume = {67},
 id = {84d47634-4289-36cb-bf55-1afe057163c5},
 created = {2020-07-31T17:58:45.217Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.407Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This brief considers both safety and efficiency issues for vehicular networked systems (VNSs) where vehicles exchange information over vehicle to vehicle (V2V) wireless communication channels. One of the challenges to ensure system safety and efficiency lies in unreliable V2V fading channel conditions, which stochastically change as a function of the vehicle states and are subject to severe data rate drops. By adopting a bursty state-dependent fading model, this brief presents a novel event-based adaptive power control scheme. Under this scheme, the VNS assures efficient use of communication resources while preserving almost sure asymptotic stability. The benefits of the proposed scheme over other power policies are shown in a leader-follower formation control example.},
 bibtype = {article},
 author = {Hu, Bin},
 doi = {10.1109/TCSII.2019.2913789},
 journal = {IEEE Transactions on Circuits and Systems II: Express Briefs},
 number = {3}
}

This brief considers both safety and efficiency issues for vehicular networked systems (VNSs) where vehicles exchange information over vehicle to vehicle (V2V) wireless communication channels. One of the challenges to ensure system safety and efficiency lies in unreliable V2V fading channel conditions, which stochastically change as a function of the vehicle states and are subject to severe data rate drops. By adopting a bursty state-dependent fading model, this brief presents a novel event-based adaptive power control scheme. Under this scheme, the VNS assures efficient use of communication resources while preserving almost sure asymptotic stability. The benefits of the proposed scheme over other power policies are shown in a leader-follower formation control example.

@inproceedings{
 title = {Design a portable sensing platform with a LiDaR and Ti ARM M4 microcontroller},
 type = {inproceedings},
 year = {2019},
 id = {538e61b7-6b4c-3cd8-8da7-221c6ef90182},
 created = {2020-07-31T17:58:45.225Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.737Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The Microcontrollers/microelectronics have been used in variety of engineering applications on complex and efficient operations. One of the challenges in applying existing microelectronic technologies to these engineering systems lies in the need of modular portability, scalability, customizability, and compatibility. This paper focuses on addressing such challenges by designing a portable sensing platform that integrates a Lidar with USB interface and TI ARM M4 microcontroller. This developed sensing system will serve as an effective teaching platform to create new or enhance existing microelectronic courses that allow students to gain hands-on experiences in mobile embedded system designs. Moreover, the customizability and portability of the embedded sensing platform can also be used for the unmanned aerial vehicles in the GPS-denied environments.},
 bibtype = {inproceedings},
 author = {Hu, Bin and Hsiung, Steve C. and Kersey, Matthew B.},
 doi = {10.18260/1-2--32588},
 booktitle = {ASEE Annual Conference and Exposition, Conference Proceedings}
}

The Microcontrollers/microelectronics have been used in variety of engineering applications on complex and efficient operations. One of the challenges in applying existing microelectronic technologies to these engineering systems lies in the need of modular portability, scalability, customizability, and compatibility. This paper focuses on addressing such challenges by designing a portable sensing platform that integrates a Lidar with USB interface and TI ARM M4 microcontroller. This developed sensing system will serve as an effective teaching platform to create new or enhance existing microelectronic courses that allow students to gain hands-on experiences in mobile embedded system designs. Moreover, the customizability and portability of the embedded sensing platform can also be used for the unmanned aerial vehicles in the GPS-denied environments.

@article{
 title = {Optimal codesign of industrial networked control systems with state-dependent correlated fading channels},
 type = {article},
 year = {2019},
 keywords = {codesign method,factory automation,networked control system,shadow fading,stochastic safety},
 pages = {4472-4493},
 volume = {29},
 id = {412b3b6d-6aa8-3bb5-8c03-d26c410582ea},
 created = {2020-07-31T17:58:45.274Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.584Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper examines a codesign problem in industrial networked control systems (NCS) whereby physical systems are controlled over wireless fading channels. The considered wireless channels are assumed to be stochastically dependent on the physical states of moving machineries in the industrial working space. In this paper, the moving machineries are modeled as Markov decision processes whereas the characteristics of the correlated fading channels are modeled as a binary random process whose probability measure depends on both the physical states of moving machineries and the transmission power of communication channels. Under such a state-dependent fading channel model, sufficient conditions to ensure the stochastic safety of the NCS are first derived. Using the derived safety conditions, a codesign problem is then formulated as a constrained joint optimization problem that seeks for optimal control and transmission power policies which simultaneously minimize an infinite time cost on both communication resource and control effort. This paper shows that such optimal policies can be obtained in a computationally efficient manner using convex programming methods. Simulation results of an autonomous forklift truck and a networked DC motor system are presented to illustrate the advantage and efficacy of the proposed codesign framework for industrial NCS.},
 bibtype = {article},
 author = {Hu, Bin and Tamba, Tua A.},
 doi = {10.1002/rnc.4643},
 journal = {International Journal of Robust and Nonlinear Control},
 number = {13}
}

This paper examines a codesign problem in industrial networked control systems (NCS) whereby physical systems are controlled over wireless fading channels. The considered wireless channels are assumed to be stochastically dependent on the physical states of moving machineries in the industrial working space. In this paper, the moving machineries are modeled as Markov decision processes whereas the characteristics of the correlated fading channels are modeled as a binary random process whose probability measure depends on both the physical states of moving machineries and the transmission power of communication channels. Under such a state-dependent fading channel model, sufficient conditions to ensure the stochastic safety of the NCS are first derived. Using the derived safety conditions, a codesign problem is then formulated as a constrained joint optimization problem that seeks for optimal control and transmission power policies which simultaneously minimize an infinite time cost on both communication resource and control effort. This paper shows that such optimal policies can be obtained in a computationally efficient manner using convex programming methods. Simulation results of an autonomous forklift truck and a networked DC motor system are presented to illustrate the advantage and efficacy of the proposed codesign framework for industrial NCS.

@inproceedings{
 title = {An Actuator Intrusion Detection Mechanism for Event-Triggered Moving Target Defense Control},
 type = {inproceedings},
 year = {2019},
 keywords = {cyber-physical systems,event triggering,moving target defense,switched control system},
 pages = {111-114},
 id = {bb653317-c668-3197-b618-c6b14a3cc735},
 created = {2020-07-31T17:58:45.716Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.572Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A detection scheme for the presence of actuator intrusions on cyber-physical systems is proposed through a combination use of a switching controller (SC) and an event-triggered control scheduling mechanism. The paper first shows the boundedness property of the system trajectories in the presence of actuator intrusion and derives an upper bound of their deviation from the trajetories that result from an optimal control law; The paper then proposes a mechanism for detecting the presence of intrusion on the system actuators.},
 bibtype = {inproceedings},
 author = {Tambad, Tua A. and Hu, Bin and Nazaruddin, Yul Y.},
 doi = {10.1109/ACDT47198.2019.9072823},
 booktitle = {Proceedings of the 2019 IEEE 6th Asian Conference on Defence Technology, ACDT 2019}
}

A detection scheme for the presence of actuator intrusions on cyber-physical systems is proposed through a combination use of a switching controller (SC) and an event-triggered control scheduling mechanism. The paper first shows the boundedness property of the system trajectories in the presence of actuator intrusion and derives an upper bound of their deviation from the trajetories that result from an optimal control law; The paper then proposes a mechanism for detecting the presence of intrusion on the system actuators.

@article{
 title = {String Stability Analysis for Vehicle Platooning Under Unreliable Communication Links With Event-Triggered Strategy},
 type = {article},
 year = {2019},
 keywords = {Event-triggered,fading channel model,unreliable communication links,vehicle platoon,Ⅎ2 string stability},
 pages = {2152-2164},
 volume = {68},
 id = {30bde7e0-0023-37bc-9632-4a8d3de5ace2},
 created = {2020-07-31T17:58:45.957Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.619Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Vehicle platooning systems are often equipped with vehicle-to-vehicle (V2V) communication technologies to improve both the road efficiency and road safety by exchanging vehicle information over wireless networks to maintain relatively small inter-vehicle distance. The road safety often relies on the quality of service delivered by the V2V communication. The V2V networks are, however, subject to channel fading and often have limited communication bandwidth. The limited bandwidth inevitably compromises the road safety as the vehicular network will easily get congested if the number of vehicles joining the network increases. To address the challenges of ensuring vehicle safety under unreliable wireless network with limited bandwidth, this paper first uses a two-state Markov chain to model the channel fading in vehicular networks. Under the Markov chain model, this paper further develops a novel distributed event triggered strategies under which the vehicle platooning system achieves stochastic Ⅎ2 string stability while ensuring an efficient use of the limited communication bandwidth. The simulation results are provided to verify the effectiveness and advantages of the proposed methods.},
 bibtype = {article},
 author = {Li, Zhicheng and Hu, Bin and Li, Ming and Luo, Gengnan},
 doi = {10.1109/TVT.2019.2891681},
 journal = {IEEE Transactions on Vehicular Technology},
 number = {3}
}

Vehicle platooning systems are often equipped with vehicle-to-vehicle (V2V) communication technologies to improve both the road efficiency and road safety by exchanging vehicle information over wireless networks to maintain relatively small inter-vehicle distance. The road safety often relies on the quality of service delivered by the V2V communication. The V2V networks are, however, subject to channel fading and often have limited communication bandwidth. The limited bandwidth inevitably compromises the road safety as the vehicular network will easily get congested if the number of vehicles joining the network increases. To address the challenges of ensuring vehicle safety under unreliable wireless network with limited bandwidth, this paper first uses a two-state Markov chain to model the channel fading in vehicular networks. Under the Markov chain model, this paper further develops a novel distributed event triggered strategies under which the vehicle platooning system achieves stochastic Ⅎ2 string stability while ensuring an efficient use of the limited communication bandwidth. The simulation results are provided to verify the effectiveness and advantages of the proposed methods.

@article{
 title = {Co-design of safe and efficient networked control systems in factory automation with state-dependent wireless fading channels},
 type = {article},
 year = {2019},
 keywords = {Factory automation,Networked control systems,State-dependent fading channel,Stochastic safety},
 pages = {334-346},
 volume = {105},
 id = {7ace606d-e23c-35cc-bd3f-01a9ed3984b9},
 created = {2020-07-31T17:58:46.207Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.481Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In factory automation, heterogeneous manufacturing processes need to be coordinated over wireless networks to achieve safety and efficiency. Wireless networks, however, are inherently unreliable due to shadow fading induced by the physical motion of the machinery. To assure both safety and efficiency, this paper proposes a state-dependent channel model that captures the interaction between the physical and communication systems. By adopting this channel model, sufficient conditions on the maximum allowable transmission interval are derived to ensure stochastic safety for a nonlinear physical system controlled over a state-dependent wireless fading channel. Under these sufficient conditions, the safety and efficiency co-design problem is formulated as a constrained cooperative game, whose equilibria represent optimal control and transmission power policies that minimize a discounted joint-cost in an infinite horizon. It is shown that the equilibria of the constrained game are solutions to a non-convex generalized geometric program, which are approximated by solving two convex programs. The optimality gap is quantified as a function of the size of the approximation region in convex programs, and asymptotically converges to zero by adopting a branch-bound algorithm. Simulation results of a networked robotic arm and a forklift truck are presented to verify the proposed co-design method.},
 bibtype = {article},
 author = {Hu, Bin and Wang, Yebin and Orlik, Philip V. and Koike-Akino, Toshiaki and Guo, Jianlin},
 doi = {10.1016/j.automatica.2019.04.009},
 journal = {Automatica}
}

In factory automation, heterogeneous manufacturing processes need to be coordinated over wireless networks to achieve safety and efficiency. Wireless networks, however, are inherently unreliable due to shadow fading induced by the physical motion of the machinery. To assure both safety and efficiency, this paper proposes a state-dependent channel model that captures the interaction between the physical and communication systems. By adopting this channel model, sufficient conditions on the maximum allowable transmission interval are derived to ensure stochastic safety for a nonlinear physical system controlled over a state-dependent wireless fading channel. Under these sufficient conditions, the safety and efficiency co-design problem is formulated as a constrained cooperative game, whose equilibria represent optimal control and transmission power policies that minimize a discounted joint-cost in an infinite horizon. It is shown that the equilibria of the constrained game are solutions to a non-convex generalized geometric program, which are approximated by solving two convex programs. The optimality gap is quantified as a function of the size of the approximation region in convex programs, and asymptotically converges to zero by adopting a branch-bound algorithm. Simulation results of a networked robotic arm and a forklift truck are presented to verify the proposed co-design method.

@inproceedings{
 title = {Conveying automation reliability and automation error type an empirical study in the cyber domain},
 type = {inproceedings},
 year = {2018},
 pages = {172-173},
 volume = {1},
 id = {955476e6-c244-394c-872f-67db9ed148b6},
 created = {2020-07-31T17:58:45.271Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.229Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Chen, Jing and Mishler, Scott and Hu, Bin},
 doi = {10.1177/1541931218621040},
 booktitle = {Proceedings of the Human Factors and Ergonomics Society}
}

@inproceedings{
 title = {Resilient control under denial-of-service via dynamic event triggering},
 type = {inproceedings},
 year = {2018},
 pages = {1749-1754},
 volume = {2018-Janua},
 id = {32294eca-f4f9-3827-8c58-85b5c9e23c63},
 created = {2020-07-31T17:58:45.753Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.524Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Networked control systems (NCS) typically utilize networks of computers and communication links to automatically monitor and manage the plant-sensor-controller-actuator interactions and data exchanges. One important issue in the design of NCS is concerning the reliability and security of the used communication network when there are problems/imperfections which occur due to failures of some components or attacks from malicious adversaries. This paper examines the NCS stability in the presence of a particular communication network problem called denial-of-service (DoS). In essence, a DoS is a form of failure/attack on NCS' communication systems which prevents an ideal implementation of the control inputs to be executed. This paper proposes a resilient control design approach based on a dynamic triggering scheme (DTS) which guarantees the stability of the closed loop NCS in the presence of DoS. The main results of the papers show that the DTS appears to be a more beneficial approach than the previously developed static triggering scheme since the former not only provides an event-triggered implementation scheme with longer inter-sampling interval but is also capable of mitigating DoS with longer (average) duration of occurrences.},
 bibtype = {inproceedings},
 author = {Tamba, Tua A. and Nazaruddin, Yul Y. and Hu, Bin},
 doi = {10.1109/ASCC.2017.8287438},
 booktitle = {2017 Asian Control Conference, ASCC 2017}
}

Networked control systems (NCS) typically utilize networks of computers and communication links to automatically monitor and manage the plant-sensor-controller-actuator interactions and data exchanges. One important issue in the design of NCS is concerning the reliability and security of the used communication network when there are problems/imperfections which occur due to failures of some components or attacks from malicious adversaries. This paper examines the NCS stability in the presence of a particular communication network problem called denial-of-service (DoS). In essence, a DoS is a form of failure/attack on NCS' communication systems which prevents an ideal implementation of the control inputs to be executed. This paper proposes a resilient control design approach based on a dynamic triggering scheme (DTS) which guarantees the stability of the closed loop NCS in the presence of DoS. The main results of the papers show that the DTS appears to be a more beneficial approach than the previously developed static triggering scheme since the former not only provides an event-triggered implementation scheme with longer inter-sampling interval but is also capable of mitigating DoS with longer (average) duration of occurrences.

@article{
 title = {The description-experience gap in the effect of warning reliability on user trust and performance in a phishing-detection context},
 type = {article},
 year = {2018},
 keywords = {Description-experience gap,Feedback,Human-automation interaction,Phishing detection,Trust},
 pages = {35-47},
 volume = {119},
 id = {914ada6c-26e6-355a-84b9-3557fc18c0b2},
 created = {2020-07-31T17:58:45.853Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.936Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {How the human user trusts and interacts with an automation system is influenced by how well the system capabilities are conveyed to the user. When interacting with the automation system, the user can obtain the system reliability information through an explicit description of the reliability or through experiencing the system over time. The term description-experience gap illustrates the difference between description-based and experience-based human decisions. In the current study, we investigated how this description-experience gap applies to human-automation interaction with a phishing-detection task in the cyber domain. In two experiments, participants’ performance in detecting phishing emails and their trust in the phishing detection system were measured when system reliability, description, and experience (i.e., feedback) were varied systematically in easy and difficult phishing detection tasks. The results suggested that system reliability had a profound influence on human performance in the system, but the benefits of having a more reliable system may depend on task difficulty. Also, providing feedback increased trust calibration in terms of both objective and subjective trust measures, yet providing description of system reliability increased only subjective trust. This result pattern not only shows the gap in the effects of feedback and description, but it also extends the description-experience gap concept from rare events to common events.},
 bibtype = {article},
 author = {Chen, Jing and Mishler, Scott and Hu, Bin and Li, Ninghui and Proctor, Robert W.},
 doi = {10.1016/j.ijhcs.2018.05.010},
 journal = {International Journal of Human Computer Studies}
}

How the human user trusts and interacts with an automation system is influenced by how well the system capabilities are conveyed to the user. When interacting with the automation system, the user can obtain the system reliability information through an explicit description of the reliability or through experiencing the system over time. The term description-experience gap illustrates the difference between description-based and experience-based human decisions. In the current study, we investigated how this description-experience gap applies to human-automation interaction with a phishing-detection task in the cyber domain. In two experiments, participants’ performance in detecting phishing emails and their trust in the phishing detection system were measured when system reliability, description, and experience (i.e., feedback) were varied systematically in easy and difficult phishing detection tasks. The results suggested that system reliability had a profound influence on human performance in the system, but the benefits of having a more reliable system may depend on task difficulty. Also, providing feedback increased trust calibration in terms of both objective and subjective trust measures, yet providing description of system reliability increased only subjective trust. This result pattern not only shows the gap in the effects of feedback and description, but it also extends the description-experience gap concept from rare events to common events.

@inproceedings{
 title = {A decision-making framework for robust multi-agent systems in risky communication scenarios},
 type = {inproceedings},
 year = {2018},
 issue = {209989},
 id = {150b18f2-4244-39ea-9b06-3770d705d667},
 created = {2020-07-31T17:58:45.981Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.955Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this paper, we present a novel decision-making framework to characterize the communication status of a distributed multi-agent system. The theoretical package dropout probability (PDP) in communication is formulated as a function of the inter-distance between agents. A statistical representation is adopted to describe the actual value of the PDP. The communication status, formulated as a binary variable, is then determined by the comparison between the theoretical PDP and its statistical representation. To handle the unexpected degradation/loss of the communication network, an algorithm is proposed to quickly examine the robustness of the communication network in the case of single-node failure, i.e., the biconnectivity of a graph. The proposed framework is tested in scenarios of changing formation and temporary- and permanent-loss of communication.},
 bibtype = {inproceedings},
 author = {Samiei, Arezoo and Hu, Bin and Zhao, Shiyu and Sun, Liang},
 doi = {10.2514/6.2018-0644},
 booktitle = {AIAA Information Systems-AIAA Infotech at Aerospace, 2018}
}

In this paper, we present a novel decision-making framework to characterize the communication status of a distributed multi-agent system. The theoretical package dropout probability (PDP) in communication is formulated as a function of the inter-distance between agents. A statistical representation is adopted to describe the actual value of the PDP. The communication status, formulated as a binary variable, is then determined by the comparison between the theoretical PDP and its statistical representation. To handle the unexpected degradation/loss of the communication network, an algorithm is proposed to quickly examine the robustness of the communication network in the case of single-node failure, i.e., the biconnectivity of a graph. The proposed framework is tested in scenarios of changing formation and temporary- and permanent-loss of communication.

@article{
 title = {Optimal Task Allocation for Human-Machine Collaborative Manufacturing Systems},
 type = {article},
 year = {2017},
 keywords = {Discrete event dynamic automation systems,Petri Nets for automation control,human factors and human-in-the-loop},
 pages = {1933-1940},
 volume = {2},
 id = {a3e0d974-58a7-3172-b541-04fbb7441b06},
 created = {2020-07-31T17:58:45.478Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.249Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Human-machine collaborative manufacturing systems consist of human operators and automated machines. They cooperate with each other to accomplish complex tasks that are difficult for either the human or machine alone. This letter considers an optimal task-allocation problem for human-machine collaborative manufacturing systems, where various tasks are dispatched to human operators and automated machines to achieve optimal joint human-system performance. Designing such optimal task allocation is challenging because of the stochastic hybrid feature of manufacturing processes, as well as varying human performance caused by physical fatigue. To address this challenge, we first model human fatigue as a continuous-time Markov decision process, which is capable of capturing stochastic uncertainties on fatigue dynamics under different task assignments. A novel controlled stochastic petri net is then proposed to model the manufacturing process, in which both time- and event-driven dynamics can be regulated by task allocation between the human and machine. Under mild assumptions, we show that the optimal task-allocation problem under the proposed human manufacturing framework can be solved by linear programming. Simulation results of a four-part assembly process are used to verify our theoretical findings.},
 bibtype = {article},
 author = {Hu, Bin and Chen, Jing},
 doi = {10.1109/LRA.2017.2714981},
 journal = {IEEE Robotics and Automation Letters},
 number = {4}
}

Human-machine collaborative manufacturing systems consist of human operators and automated machines. They cooperate with each other to accomplish complex tasks that are difficult for either the human or machine alone. This letter considers an optimal task-allocation problem for human-machine collaborative manufacturing systems, where various tasks are dispatched to human operators and automated machines to achieve optimal joint human-system performance. Designing such optimal task allocation is challenging because of the stochastic hybrid feature of manufacturing processes, as well as varying human performance caused by physical fatigue. To address this challenge, we first model human fatigue as a continuous-time Markov decision process, which is capable of capturing stochastic uncertainties on fatigue dynamics under different task assignments. A novel controlled stochastic petri net is then proposed to model the manufacturing process, in which both time- and event-driven dynamics can be regulated by task allocation between the human and machine. Under mild assumptions, we show that the optimal task-allocation problem under the proposed human manufacturing framework can be solved by linear programming. Simulation results of a four-part assembly process are used to verify our theoretical findings.

@inproceedings{
 title = {An event-triggering-based approach for three-dimensional local-level frame formation control of leader-follower UAVs},
 type = {inproceedings},
 year = {2017},
 pages = {472-479},
 id = {331b865c-9b1f-30ed-b402-cdacd1c1e50d},
 created = {2020-07-31T17:58:45.766Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.564Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The development of a three-dimensional (3D) formation controller for unmanned aerial vehicles (UAVs) associated with an event-triggered transmission protocol is presented in this paper. The formation controller is derived based on a 3D relative kinematic model established upon a local-level coordinate frame, which does not require any absolute global information. The proposed controller is developed using the Lyapunov theory and proved to be capable of driving the follower UAV to exponentially converge to a desired formation. An event-triggered transmission protocol is developed based on the derived 3D formation controller in order to efficiently schedule the transmission of the leader's state to the follower according to the dynamic change of the leader's state. The performance of the formation control law integrated with the event-triggered protocol is verified in simulation.},
 bibtype = {inproceedings},
 author = {Sun, Liang and Hu, Bin and Zhao, Shiyu},
 doi = {10.1109/ICUAS.2017.7991341},
 booktitle = {2017 International Conference on Unmanned Aircraft Systems, ICUAS 2017}
}

The development of a three-dimensional (3D) formation controller for unmanned aerial vehicles (UAVs) associated with an event-triggered transmission protocol is presented in this paper. The formation controller is derived based on a 3D relative kinematic model established upon a local-level coordinate frame, which does not require any absolute global information. The proposed controller is developed using the Lyapunov theory and proved to be capable of driving the follower UAV to exponentially converge to a desired formation. An event-triggered transmission protocol is developed based on the derived 3D formation controller in order to efficiently schedule the transmission of the leader's state to the follower according to the dynamic change of the leader's state. The performance of the formation control law integrated with the event-triggered protocol is verified in simulation.

@inproceedings{
 title = {Toward efficient manufacturing systems: A trust based human robot collaboration},
 type = {inproceedings},
 year = {2017},
 pages = {1536-1541},
 id = {67db31bc-0f33-3bff-9e38-65c85dc98632},
 created = {2020-07-31T17:58:45.802Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.600Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Modern manufacturing systems are human robot systems that consist of human operators and intelligent robots collaborating with each other to accomplish complex tasks. The system performance of such human robot systems relies heavily on reliable and efficient human robot collaborations, which may be seriously compromised due to temporal variations in human to robot trust. This paper proposes to model the human trust as a Markov Decision Process (MDP) to capture its dynamic uncertainties on how the robot performance affects the human trust. The system performance under such trust based human robot collaboration is formulated as an optimization problem where an optimal task allocation policy is obtained to minimize the expected average cost on each cycle of the persistent tasks while maximizing the probability of satisfying Linear Temporal Logic specifications. The case study of an assembly process shows the effectiveness and benefits of our proposed trust based human robot collaboration.},
 bibtype = {inproceedings},
 author = {Wu, Bo and Hu, Bin and Lin, Hai},
 doi = {10.23919/ACC.2017.7963171},
 booktitle = {Proceedings of the American Control Conference}
}

Modern manufacturing systems are human robot systems that consist of human operators and intelligent robots collaborating with each other to accomplish complex tasks. The system performance of such human robot systems relies heavily on reliable and efficient human robot collaborations, which may be seriously compromised due to temporal variations in human to robot trust. This paper proposes to model the human trust as a Markov Decision Process (MDP) to capture its dynamic uncertainties on how the robot performance affects the human trust. The system performance under such trust based human robot collaboration is formulated as an optimization problem where an optimal task allocation policy is obtained to minimize the expected average cost on each cycle of the persistent tasks while maximizing the probability of satisfying Linear Temporal Logic specifications. The case study of an assembly process shows the effectiveness and benefits of our proposed trust based human robot collaboration.

@inproceedings{
 title = {Recognition of car warnings: An analysis of various alert types},
 type = {inproceedings},
 year = {2017},
 keywords = {Auditory icons,Car alerts,Sonification,Spearcons,Text-to-speech,Warning systems},
 pages = {2010-2016},
 volume = {Part F1276},
 id = {1523553b-baea-372a-9415-c44c933969d6},
 created = {2020-07-31T17:58:46.011Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.625Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Warnings are integral to ensuring the safe operation of a vehicle. The use of auditory alerts and warnings has the potential to alleviate drivers' workload, increase drivers' situation awareness, and facilitate efficient and safe driving. The present study assessed the ability of individuals to react to auditory warnings. The warnings took the form of text-to-speech (TTS), spearcons at two levels of linear compression, and auditory icons. To assess usability, the NASA Task Load Index and an annoyance question were used. Participants pressed a space bar when they recognized a warning, and then identified auditory warnings by selecting a picture corresponding to the meaning of the warning. The results showed that participants responded to the fastest spearcon warnings more quickly compared to TTS and auditory icons. Responses to auditory icons were slowest compared to all other auditory types. Importantly, responses to spearcon warnings were no less accurate in comparison to TTS warnings.},
 bibtype = {inproceedings},
 author = {Sabic, Edin and Mishler, Scott and Chen, Jing and Hu, Bin},
 doi = {10.1145/3027063.3053149},
 booktitle = {Conference on Human Factors in Computing Systems - Proceedings}
}

Warnings are integral to ensuring the safe operation of a vehicle. The use of auditory alerts and warnings has the potential to alleviate drivers' workload, increase drivers' situation awareness, and facilitate efficient and safe driving. The present study assessed the ability of individuals to react to auditory warnings. The warnings took the form of text-to-speech (TTS), spearcons at two levels of linear compression, and auditory icons. To assess usability, the NASA Task Load Index and an annoyance question were used. Participants pressed a space bar when they recognized a warning, and then identified auditory warnings by selecting a picture corresponding to the meaning of the warning. The results showed that participants responded to the fastest spearcon warnings more quickly compared to TTS and auditory icons. Responses to auditory icons were slowest compared to all other auditory types. Importantly, responses to spearcon warnings were no less accurate in comparison to TTS warnings.

@misc{
 title = {A learning based optimal human robot collaboration with linear temporal logic constraints},
 type = {misc},
 year = {2017},
 source = {arXiv},
 id = {df0db95d-4285-3d5c-9965-89d2f060aaf2},
 created = {2020-10-27T23:59:00.000Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.481Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {—This paper considers an optimal task allocation problem for human robot collaboration in human robot systems with persistent tasks. Such human robot systems consist of human operators and intelligent robots collaborating with each other to accomplish complex tasks that cannot be done by either part alone. The system objective is to maximize the probability of successfully executing persistent tasks that are formulated as linear temporal logic specifications and minimize the average cost between consecutive visits of a particular proposition. This paper proposes to model the human robot collaboration under a framework with the composition of multiple Markov Decision Process (MDP) with possibly unknown transition probabilities, which characterizes how human cognitive states, such as human trust and fatigue, stochastically change with the robot performance. Under the unknown MDP models, an algorithm is developed to learn the model and obtain an optimal task allocation policy that minimizes the expected average cost for each task cycle and maximizes the probability of satisfying linear temporal logic constraints. Moreover, this paper shows that the difference between the optimal policy based on the learned model and that based on the underlying ground truth model can be bounded by arbitrarily small constant and large confidence level with sufficient samples. The case study of an assembly process demonstrates the effectiveness and benefits of our proposed learning based human robot collaboration.},
 bibtype = {misc},
 author = {Wu, Bo and Hu, Bin and Lin, Hai}
}

—This paper considers an optimal task allocation problem for human robot collaboration in human robot systems with persistent tasks. Such human robot systems consist of human operators and intelligent robots collaborating with each other to accomplish complex tasks that cannot be done by either part alone. The system objective is to maximize the probability of successfully executing persistent tasks that are formulated as linear temporal logic specifications and minimize the average cost between consecutive visits of a particular proposition. This paper proposes to model the human robot collaboration under a framework with the composition of multiple Markov Decision Process (MDP) with possibly unknown transition probabilities, which characterizes how human cognitive states, such as human trust and fatigue, stochastically change with the robot performance. Under the unknown MDP models, an algorithm is developed to learn the model and obtain an optimal task allocation policy that minimizes the expected average cost for each task cycle and maximizes the probability of satisfying linear temporal logic constraints. Moreover, this paper shows that the difference between the optimal policy based on the learned model and that based on the underlying ground truth model can be bounded by arbitrarily small constant and large confidence level with sufficient samples. The case study of an assembly process demonstrates the effectiveness and benefits of our proposed learning based human robot collaboration.

@inproceedings{
 title = {Event-triggering in three-dimensional leader-follower formation control for unmanned aerial vehicles},
 type = {inproceedings},
 year = {2016},
 volume = {2},
 id = {178ef297-6d31-3169-a862-5e8749a9ce38},
 created = {2020-07-31T17:58:45.482Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.317Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper addresses a three-dimensional (3D) leader-follower formation control problem where an event-triggered transmission scheme is developed to schedule the information exchange between the leader and follower unmanned aerial vehicles (UAVs). A novel 3D model based on a local level spherical frame is developed to characterize the relative dynamics of the leader and follower UAVs. Based on this 3D model, a novel nonlinear tracking control law is developed to achieve an exponential tracking performance of the system. An event-triggered communication scheduling scheme is adopted under the proposed 3D leader-follower framework in order to achieve an efficient use of communication bandwidth by adapting the transmission time for the changes on UAV states. The stability of the formation control law and the efficiency of the event-triggered method are verified and demonstrated in simulation.},
 bibtype = {inproceedings},
 author = {Sun, Liang and Hu, Bin},
 doi = {10.1115/DSCC2016-9783},
 booktitle = {ASME 2016 Dynamic Systems and Control Conference, DSCC 2016}
}

This paper addresses a three-dimensional (3D) leader-follower formation control problem where an event-triggered transmission scheme is developed to schedule the information exchange between the leader and follower unmanned aerial vehicles (UAVs). A novel 3D model based on a local level spherical frame is developed to characterize the relative dynamics of the leader and follower UAVs. Based on this 3D model, a novel nonlinear tracking control law is developed to achieve an exponential tracking performance of the system. An event-triggered communication scheduling scheme is adopted under the proposed 3D leader-follower framework in order to achieve an efficient use of communication bandwidth by adapting the transmission time for the changes on UAV states. The stability of the formation control law and the efficiency of the event-triggered method are verified and demonstrated in simulation.

@article{
 title = {Distributed Switching Control to Achieve Almost Sure Safety for Leader-Follower Vehicular Networked Systems},
 type = {article},
 year = {2015},
 keywords = {Cyber-physical systems (CPS),quality of service (QoS),vehicular network (VN)},
 pages = {3195-3209},
 volume = {60},
 id = {e3951c21-0949-3c40-bfae-9f0a63dffbf2},
 created = {2016-04-04T21:54:59.000Z},
 file_attached = {true},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.614Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Leader-follower formation control is a widely used distributed control strategy that requires systems to exchange their information over a wireless radio communication network to attain and maintain formations. These wireless networks are often subject to deep fades, where a severe drop in the quality of the communication link occurs. Such deep fades inevitably inject a great deal of stochastic uncertainties into the system, which significantly impact the system's performance and stability, and cause unexpected safety problems in applications like smart transportation systems. Assuming an exponentially bursty channel that varies as a function of the vehicular states, this paper proposes a distributed switching control scheme under which the local controller is reconfigured in response to the changes of channel state, to assure almost sure safety for a chain of leader-follower system. Here almost sure safety means that the likelihood of vehicular states entering a safe region asymptotically goes to one as time goes to infinity. Sufficient conditions are provided for each local vehicle to decide which controller is placed in the feedback loop to assure almost sure safety in the presence of deep fades. Simulation results of a chain of leader-follower formation are used to illustrate the findings.},
 bibtype = {article},
 author = {Hu, Bin and Lemmon, Michael D.},
 doi = {10.1109/TAC.2015.2418451},
 journal = {IEEE Transactions on Automatic Control},
 number = {12}
}

Leader-follower formation control is a widely used distributed control strategy that requires systems to exchange their information over a wireless radio communication network to attain and maintain formations. These wireless networks are often subject to deep fades, where a severe drop in the quality of the communication link occurs. Such deep fades inevitably inject a great deal of stochastic uncertainties into the system, which significantly impact the system's performance and stability, and cause unexpected safety problems in applications like smart transportation systems. Assuming an exponentially bursty channel that varies as a function of the vehicular states, this paper proposes a distributed switching control scheme under which the local controller is reconfigured in response to the changes of channel state, to assure almost sure safety for a chain of leader-follower system. Here almost sure safety means that the likelihood of vehicular states entering a safe region asymptotically goes to one as time goes to infinity. Sufficient conditions are provided for each local vehicle to decide which controller is placed in the feedback loop to assure almost sure safety in the presence of deep fades. Simulation results of a chain of leader-follower formation are used to illustrate the findings.

@inproceedings{
 title = {Event triggering in vehicular networked systems with limited bandwidth and deep fading},
 type = {inproceedings},
 year = {2014},
 pages = {3542-3547},
 volume = {2015-Febru},
 issue = {February},
 id = {b5294b52-4d25-3d6e-b328-1ecc16615140},
 created = {2020-07-31T17:58:45.538Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.093Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Vehicular networked systems consist of numerous vehicles exchanging information over a wireless communication channel. These wireless communication channels are often subject to limited bandwidth and deep fading. Prior work shows that event triggering can generate, on average, larger transmission time interval than periodic scheme by triggering the transmission as a function of the sampled state. However, it is unclear whether this state-dependent transmission approach still outperforms the periodic scheme in vehicular networked system where the communication channel often fails to reliably deliver the sampled state due to deep fades. By adopting a bursty fading channel model, this paper presents a new event triggering scheme under which the vehicular system assures a larger transmission time interval than that of periodic scheme while preserving almost sure asymptotic stability in the absence of disturbance, and practical stability in probability with bounded disturbance. In the disturbance free case, the triggering law guarantees increasing transmission time interval as system approaches its equilibrium. In the bounded disturbance case, the probability of system state leaving a bounded set is a function of the transmission time interval, disturbance amplitude, and system's convergence rate. The simulation results of a leader follower example verify the theoretical findings in this paper.},
 bibtype = {inproceedings},
 author = {Hu, Bin and Lemmon, Michael D.},
 doi = {10.1109/CDC.2014.7039939},
 booktitle = {Proceedings of the IEEE Conference on Decision and Control}
}

Vehicular networked systems consist of numerous vehicles exchanging information over a wireless communication channel. These wireless communication channels are often subject to limited bandwidth and deep fading. Prior work shows that event triggering can generate, on average, larger transmission time interval than periodic scheme by triggering the transmission as a function of the sampled state. However, it is unclear whether this state-dependent transmission approach still outperforms the periodic scheme in vehicular networked system where the communication channel often fails to reliably deliver the sampled state due to deep fades. By adopting a bursty fading channel model, this paper presents a new event triggering scheme under which the vehicular system assures a larger transmission time interval than that of periodic scheme while preserving almost sure asymptotic stability in the absence of disturbance, and practical stability in probability with bounded disturbance. In the disturbance free case, the triggering law guarantees increasing transmission time interval as system approaches its equilibrium. In the bounded disturbance case, the probability of system state leaving a bounded set is a function of the transmission time interval, disturbance amplitude, and system's convergence rate. The simulation results of a leader follower example verify the theoretical findings in this paper.

@inproceedings{
 title = {Distributed switched supervisory control to achieve almost sure safety for a class of interconnected networked systems},
 type = {inproceedings},
 year = {2014},
 pages = {851-856},
 id = {367cc1f9-0349-3be7-97aa-0b7cd73ea1bf},
 created = {2020-07-31T17:58:45.542Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.212Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {An interconnected wireless networked system consists of numerous coupled subsystems that need to exchange information over wireless communication channels. The use of these wireless networks induces a great deal of stochastic uncertainty that often results from deep fades, where a severe drop in the quality of communication link occurs. Such uncertainty negatively impacts the system's performance and causes unexpected safety issues. This paper proposes a distributed switched supervisory control scheme under which the local controller is reconfigured in response to the changes of channel state, to assure almost sure safety for the interconnected system. Here, almost sure safety means that the likelihood of the system state entering a safe region asymptotically goes to one as time goes to infinity. Sufficient conditions are provided for each local supervisor to determine when and which controller is placed in the feedback loop to assure almost sure safety in the presence of deep fades. © 2014 IEEE.},
 bibtype = {inproceedings},
 author = {Hu, Bin and Lemmon, Michael D.},
 doi = {10.1109/ICCA.2014.6871032},
 booktitle = {IEEE International Conference on Control and Automation, ICCA}
}

An interconnected wireless networked system consists of numerous coupled subsystems that need to exchange information over wireless communication channels. The use of these wireless networks induces a great deal of stochastic uncertainty that often results from deep fades, where a severe drop in the quality of communication link occurs. Such uncertainty negatively impacts the system's performance and causes unexpected safety issues. This paper proposes a distributed switched supervisory control scheme under which the local controller is reconfigured in response to the changes of channel state, to assure almost sure safety for the interconnected system. Here, almost sure safety means that the likelihood of the system state entering a safe region asymptotically goes to one as time goes to infinity. Sufficient conditions are provided for each local supervisor to determine when and which controller is placed in the feedback loop to assure almost sure safety in the presence of deep fades. © 2014 IEEE.

@inproceedings{
 title = {Distributed switching control to achieve resilience to deep fades in leader-follower nonholonomic systems},
 type = {inproceedings},
 year = {2014},
 keywords = {Almost sure practical stability,Channel state information,Deep fading,Distributed switching control,Resilience},
 pages = {95-104},
 id = {ef462ff2-2d49-3d46-938c-eb537eac7241},
 created = {2020-07-31T17:58:45.590Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.952Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Leader-follower formation control is a widely used distributed control strategy that often needs systems to exchange information over a wireless radio communication network to coordinate their formations. These wireless networks are subject to deep fades, where a severe drop in the quality of the communication link occurs. Such deep fades may significantly impact the formation's performance and stability, and cause unexpected safety problems. In many applications, however, the variation in channel state is a function of the system's kinematic states. This suggests that channel state information can be used as a feedback signal to recover the performance loss caused by a deep fade. Assuming an exponentially bursty channel model, this paper proposes a distributed switching scheme under which a string of leader-follower nonholonomic system is almost surely practical stable in the presence of deep fades. Sufficient conditions are derived for each vehicle in the leader follower chain to decide which controller is placed in the feedback loop to assure almost sure practical stability. Simulation results are used to illustrate the main findings in the paper. Copyright 2014 ACM.},
 bibtype = {inproceedings},
 author = {Hu, Bin and Lemmon, Michael D.},
 doi = {10.1145/2566468.2566473},
 booktitle = {HiCoNS 2014 - Proceedings of the 3rd International Conference on High Confidence Networked Systems (Part of CPS Week)}
}

Leader-follower formation control is a widely used distributed control strategy that often needs systems to exchange information over a wireless radio communication network to coordinate their formations. These wireless networks are subject to deep fades, where a severe drop in the quality of the communication link occurs. Such deep fades may significantly impact the formation's performance and stability, and cause unexpected safety problems. In many applications, however, the variation in channel state is a function of the system's kinematic states. This suggests that channel state information can be used as a feedback signal to recover the performance loss caused by a deep fade. Assuming an exponentially bursty channel model, this paper proposes a distributed switching scheme under which a string of leader-follower nonholonomic system is almost surely practical stable in the presence of deep fades. Sufficient conditions are derived for each vehicle in the leader follower chain to decide which controller is placed in the feedback loop to assure almost sure practical stability. Simulation results are used to illustrate the main findings in the paper. Copyright 2014 ACM.

@inproceedings{
 title = {Using channel state feedback to achieve resilience to deep fades in wireless networked control systems},
 type = {inproceedings},
 year = {2013},
 keywords = {almost sure stability,channel state information,deep fading,resilience,wireless networked control systems},
 pages = {41-48},
 id = {c85c1a74-712c-3441-bb24-58da40cbbd0c},
 created = {2020-07-31T17:58:45.593Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.610Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Wireless networked control systems (WNCS) consist of several dynamical systems that exchange information over a wireless radio (RF) communication network. These RF networks are subject to deep fades where the effective link throughput drops precipitously. Deep fading negatively impacts WNCS performance and stability, but in many applications the probability of a deep fade is a function of the system state. This suggests that one can use channel state information (CSI) as a feedback signal to recover some of the performance lost. This paper derives necessary and sufficient conditions for the almost sure stability of WNCS in the presence of deep fading. These conditions relate the channel's state to the WNCS's convergence rate. This paper uses this fact to reconfigure WNCS controllers to recover system performance in the presence of such fades. The results are illustrated using a leader-follower scenario found in vehicle-to-vehicle (V2V) applications. © 2013 ACM.},
 bibtype = {inproceedings},
 author = {Hu, Bin and Lemmon, Michael D.},
 doi = {10.1145/2461446.2461453},
 booktitle = {HiCoNS 2013 - Proceedings of the 2nd ACM International Conference on High Confidence Networked Systems, Part of CPS Week 2013}
}

Wireless networked control systems (WNCS) consist of several dynamical systems that exchange information over a wireless radio (RF) communication network. These RF networks are subject to deep fades where the effective link throughput drops precipitously. Deep fading negatively impacts WNCS performance and stability, but in many applications the probability of a deep fade is a function of the system state. This suggests that one can use channel state information (CSI) as a feedback signal to recover some of the performance lost. This paper derives necessary and sufficient conditions for the almost sure stability of WNCS in the presence of deep fading. These conditions relate the channel's state to the WNCS's convergence rate. This paper uses this fact to reconfigure WNCS controllers to recover system performance in the presence of such fades. The results are illustrated using a leader-follower scenario found in vehicle-to-vehicle (V2V) applications. © 2013 ACM.

@article{
 title = {Multi-loop nonlinear internal model controller design based on a dynamic fuzzy partial least squares model},
 type = {article},
 year = {2013},
 keywords = {Internal model control,MCH distillation column,PH neutralization,Partial least squares,TSK fuzzy model},
 pages = {2559-2568},
 volume = {91},
 id = {52cf88b3-7624-30cb-8610-ab5be5792458},
 created = {2020-07-31T17:58:46.029Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.954Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this paper, a dynamic fuzzy partial least squares (DFPLS) modeling method is proposed. Under such framework, the multiple input multiple output (MIMO) nonlinear system can be automatically decomposed into several univariate subsystems in PLS latent space. Within each latent space, a dynamic fuzzy method is introduced to model the inherent dynamic and nonlinear feature of the physical system. The new modeling method combines the decoupling characteristic of PLS framework and the ability of dynamic nonlinear modeling in the fuzzy method. Based on the DFPLS model, a multi-loop nonlinear internal model control (IMC) strategy is proposed. A pH neutralization process and a methylcyclohexane (MCH) distillation column from Aspen Dynamic Module are presented to demonstrate the effectiveness of the proposed modeling method and control strategy. © 2013 The Institution of Chemical Engineers.},
 bibtype = {article},
 author = {Chi, Qinghua and Zhao, Zhao and Hu, Bin and Lv, Yan and Liang, Jun},
 doi = {10.1016/j.cherd.2013.04.019},
 journal = {Chemical Engineering Research and Design},
 number = {12}
}

In this paper, a dynamic fuzzy partial least squares (DFPLS) modeling method is proposed. Under such framework, the multiple input multiple output (MIMO) nonlinear system can be automatically decomposed into several univariate subsystems in PLS latent space. Within each latent space, a dynamic fuzzy method is introduced to model the inherent dynamic and nonlinear feature of the physical system. The new modeling method combines the decoupling characteristic of PLS framework and the ability of dynamic nonlinear modeling in the fuzzy method. Based on the DFPLS model, a multi-loop nonlinear internal model control (IMC) strategy is proposed. A pH neutralization process and a methylcyclohexane (MCH) distillation column from Aspen Dynamic Module are presented to demonstrate the effectiveness of the proposed modeling method and control strategy. © 2013 The Institution of Chemical Engineers.

@inproceedings{
 title = {Multi-loop nonlinear internal model controller design under nonlinear dynamic PLS framework using ARX-neural network model},
 type = {inproceedings},
 year = {2012},
 keywords = {ARX-NN structure,Aspen Dynamic Module,MCH distillation column,Nonlinear IMC scheme,Partial least squares},
 pages = {207-217},
 volume = {22},
 issue = {1},
 id = {8004b7c6-b616-37a9-b0e8-656adee30b61},
 created = {2020-07-31T17:58:45.651Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.220Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this paper, a novel multi-loop nonlinear internal model control (IMC) strategy for multiple-input multiple-output (MIMO) systems is presented under the partial least squares (PLS) framework, which automatically decomposes the system into several univariate subsystems in the latent space. To formulate a nonlinear dynamic PLS framework, we propose an ARX-neural network (ARX-NN) cascaded structure, and incorporate it into PLS inner model. A gradient-based optimization approach is then provided to identify the parameter sets of the ARX-NN PLS model so that the plant-model mismatch is minimized. Furthermore, with perfect model, we show that the response of the closed loop system can be reduced to a simple linear IMC filter with the original system delay. The simulation results of a methylcyclohexane (MCH) distillation column from Aspen Dynamic Module, demonstrate the effectiveness of our approach in terms of disturbance rejection and tracking performance. © 2011 Elsevier Ltd. All Rights Reserved.},
 bibtype = {inproceedings},
 author = {Hu, Bin and Zhao, Zhao and Liang, Jun},
 doi = {10.1016/j.jprocont.2011.09.002},
 booktitle = {Journal of Process Control}
}

In this paper, a novel multi-loop nonlinear internal model control (IMC) strategy for multiple-input multiple-output (MIMO) systems is presented under the partial least squares (PLS) framework, which automatically decomposes the system into several univariate subsystems in the latent space. To formulate a nonlinear dynamic PLS framework, we propose an ARX-neural network (ARX-NN) cascaded structure, and incorporate it into PLS inner model. A gradient-based optimization approach is then provided to identify the parameter sets of the ARX-NN PLS model so that the plant-model mismatch is minimized. Furthermore, with perfect model, we show that the response of the closed loop system can be reduced to a simple linear IMC filter with the original system delay. The simulation results of a methylcyclohexane (MCH) distillation column from Aspen Dynamic Module, demonstrate the effectiveness of our approach in terms of disturbance rejection and tracking performance. © 2011 Elsevier Ltd. All Rights Reserved.

@inproceedings{
 title = {Resilient event triggered systems with limited communication},
 type = {inproceedings},
 year = {2012},
 pages = {6577-6582},
 id = {88152632-4c10-37cc-9b27-fd88664533cf},
 created = {2020-07-31T17:58:45.815Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.218Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A resilient control system is one that maintains state awareness and an accepted level of operational normalcy in response to unexpected disturbances. There has recently been great interest in event-triggered control for networked systems. It is unclear, however, whether event-triggering is appropriate for resilient control because of the sporadic nature of the feedback. This paper examines the bit-rates needed to realize event-triggered systems that are resilient to transient faults. Using techniques from dynamically quantized control, we derive sufficient resilient bit-rates for nonlinear scalar systems with affine controls and disturbances. For linear systems, these sufficient rates are necessary for stabilizability. The results in this paper suggest that, at least for transient faults, resilient control is indeed achievable using event-triggered feedback. © 2012 IEEE.},
 bibtype = {inproceedings},
 author = {Li, Lichun and Hu, Bin and Lemmon, Michael},
 doi = {10.1109/CDC.2012.6426151},
 booktitle = {Proceedings of the IEEE Conference on Decision and Control}
}

A resilient control system is one that maintains state awareness and an accepted level of operational normalcy in response to unexpected disturbances. There has recently been great interest in event-triggered control for networked systems. It is unclear, however, whether event-triggering is appropriate for resilient control because of the sporadic nature of the feedback. This paper examines the bit-rates needed to realize event-triggered systems that are resilient to transient faults. Using techniques from dynamically quantized control, we derive sufficient resilient bit-rates for nonlinear scalar systems with affine controls and disturbances. For linear systems, these sufficient rates are necessary for stabilizability. The results in this paper suggest that, at least for transient faults, resilient control is indeed achievable using event-triggered feedback. © 2012 IEEE.

@article{
 title = {ARX-NNPLS model based optimization strategy and its application in polymer grade transition process},
 type = {article},
 year = {2012},
 keywords = {ARX-NN structure,Dynamic optimization,Grade transition,Partial least squares,Polymerization},
 pages = {971-979},
 volume = {20},
 id = {ebdf063d-588b-300d-bfb2-c6a17b5d87a1},
 created = {2020-07-31T17:58:45.862Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.408Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Since it is often difficult to build differential algebraic equations (DAEs) for chemical processes, a new data-based modeling approach is proposed using ARX (AutoRegressive with eXogenous inputs) combined with neural network under partial least squares framework (ARX-NNPLS), in which less specific knowledge of the process is required but the input and output data. To represent the dynamic and nonlinear behavior of the process, the ARX combined with neural network is used in the partial least squares (PLS) inner model between input and output latent variables. In the proposed dynamic optimization strategy based on the ARX-NNPLS model, neither parameterization nor iterative solving process for DAEs is needed as the ARX-NNPLS model gives a proper representation for the dynamic behavior of the process, and the computing time is greatly reduced compared to conventional control vector parameterization method. To demonstrate the ARX-NNPLS model based optimization strategy, the polyethylene grade transition in gas phase fluidized-bed reactor is taken into account. The optimization results show that the final optimal trajectory of quality index determined by the new approach moves faster to the target values and the computing time is much less.},
 bibtype = {article},
 author = {Fei, Zhengshun and Hu, Bin and Ye, Lubin and Liang, Jun},
 doi = {10.1016/S1004-9541(12)60425-X},
 journal = {Chinese Journal of Chemical Engineering},
 number = {5}
}

Since it is often difficult to build differential algebraic equations (DAEs) for chemical processes, a new data-based modeling approach is proposed using ARX (AutoRegressive with eXogenous inputs) combined with neural network under partial least squares framework (ARX-NNPLS), in which less specific knowledge of the process is required but the input and output data. To represent the dynamic and nonlinear behavior of the process, the ARX combined with neural network is used in the partial least squares (PLS) inner model between input and output latent variables. In the proposed dynamic optimization strategy based on the ARX-NNPLS model, neither parameterization nor iterative solving process for DAEs is needed as the ARX-NNPLS model gives a proper representation for the dynamic behavior of the process, and the computing time is greatly reduced compared to conventional control vector parameterization method. To demonstrate the ARX-NNPLS model based optimization strategy, the polyethylene grade transition in gas phase fluidized-bed reactor is taken into account. The optimization results show that the final optimal trajectory of quality index determined by the new approach moves faster to the target values and the computing time is much less.

@article{
 title = {Multi-loop adaptive internal model control based on a dynamic partial least squares model},
 type = {article},
 year = {2011},
 keywords = {Adaptive internal model control (IMC),Partial least squares (PLS),Recursive least squares (RLS)},
 pages = {190-200},
 volume = {12},
 id = {7c2e7a46-a76b-36c2-b714-b046f688af15},
 created = {2020-07-31T17:58:45.651Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.319Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) framework is proposed to account for plant model errors caused by slow aging, drift in operational conditions, or environmental changes. Since PLS decomposition structure enables multi-loop controller design within latent spaces, a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space. In each latent subspace, once the model error exceeds a specific threshold, online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares (RLS) algorithm. Because the IMC extracts the inverse of the minimum part of the internal model as its structure, the IMC controller is self-tuned by explicitly updating the parameters, which are parts of the internal model. Both parameter convergence and system stability are briefly analyzed, and proved to be effective. Finally, the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output (MIMO) system with pure delay. © Zhejiang University and Springer-Verlag Berlin Heidelberg 2011.},
 bibtype = {article},
 author = {Zhao, Zhao and Hu, Bin and Liang, Jun},
 doi = {10.1631/jzus.A1000316},
 journal = {Journal of Zhejiang University: Science A},
 number = {3}
}

A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) framework is proposed to account for plant model errors caused by slow aging, drift in operational conditions, or environmental changes. Since PLS decomposition structure enables multi-loop controller design within latent spaces, a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space. In each latent subspace, once the model error exceeds a specific threshold, online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares (RLS) algorithm. Because the IMC extracts the inverse of the minimum part of the internal model as its structure, the IMC controller is self-tuned by explicitly updating the parameters, which are parts of the internal model. Both parameter convergence and system stability are briefly analyzed, and proved to be effective. Finally, the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output (MIMO) system with pure delay. © Zhejiang University and Springer-Verlag Berlin Heidelberg 2011.

@article{
 title = {Nonlinear semi-parametric modeling method based on GA-ANN},
 type = {article},
 year = {2011},
 keywords = {Artificial neural network(ANN),Genetic algorithm (GA),Nonlinear system,Semi-parametric model},
 pages = {977-983},
 volume = {45},
 id = {ee4d8d40-d834-326b-9211-5849c6caff17},
 created = {2020-07-31T17:58:46.065Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.678Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Nonlinear semi-parametric models are introduced for industrial process modeling to improve the modeling accuracy by taking the advantages of both parameter and non-parameter models. The modeling methodology and structure of nonlinear semi-parametric modeling are proposed based on the genetic algorithm and the neural network, and the cross-loop iterative algorithm procedures are also introduced for estimating the parameters of both the parametric and non-parametric parts. Then, the design of neural network and the genetic algorithm are investigated, which increase the elite preserving strategy, enhance the memory function, propose an innovative fitness calculation method, and improve the crossover and mutation strategy. The on-site industrial data of polyethylene plant is used to demonstrate the effective of this method. The result shows that the proposed approach is more accurate in prediction than the conventional parametric models and can better track the variation of the process.},
 bibtype = {article},
 author = {Duan, Bin and Liang, Jun and Fei, Zheng Shun and Yang, Min and Hu, Bin},
 doi = {10.3785/j.issn.1008-973X.2011.06.003},
 journal = {Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science)},
 number = {6}
}

Nonlinear semi-parametric models are introduced for industrial process modeling to improve the modeling accuracy by taking the advantages of both parameter and non-parameter models. The modeling methodology and structure of nonlinear semi-parametric modeling are proposed based on the genetic algorithm and the neural network, and the cross-loop iterative algorithm procedures are also introduced for estimating the parameters of both the parametric and non-parametric parts. Then, the design of neural network and the genetic algorithm are investigated, which increase the elite preserving strategy, enhance the memory function, propose an innovative fitness calculation method, and improve the crossover and mutation strategy. The on-site industrial data of polyethylene plant is used to demonstrate the effective of this method. The result shows that the proposed approach is more accurate in prediction than the conventional parametric models and can better track the variation of the process.

@article{
 title = {Multi-loop internal model controller design based on a dynamic PLS framework},
 type = {article},
 year = {2010},
 keywords = {disturbance rejection,internal model controller,latent subspace,partial least squares,servo behavior},
 pages = {277-285},
 volume = {18},
 id = {6871974e-35e5-3b0e-a0ea-9058e9e86f37},
 created = {2020-07-31T17:58:45.703Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.924Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {In this paper, a multi-loop internal model control (IMC) scheme in conjunction with feed-forward strategy based on the dynamic partial least squares (DyPLS) framework is proposed. Unlike the traditional methods to decouple multi-input multi-output (MIMO) systems, the DyPLS framework automatically decomposes the MIMO process into a multi-loop system in the PLS subspace in the modeling stage. The dynamic filters with identical structure are used to build the dynamic PLS model, which retains the orthogonality among the latent variables. To address the model mismatch problem, an off-line least squares method is applied to obtain a set of optimal filter parameters in each latent space. Without losing the merits of model-based control, a simple and easy-tuned IMC structure is readily carried over to the dynamic PLS control framework. In addition, by projecting the measurable disturbance into the latent subspace, a multi-loop feed-forward control is yielded to achieve better performance for disturbance rejection. Simulation results of a distillation column are used to further demonstrate this new strategy outperforms conventional control schemes in servo behavior and disturbance rejection. © 2010 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press (CIP).},
 bibtype = {article},
 author = {Hu, Bin and Zheng, Pingyou and Liang, Jun},
 doi = {10.1016/S1004-9541(08)60353-5},
 journal = {Chinese Journal of Chemical Engineering},
 number = {2}
}

In this paper, a multi-loop internal model control (IMC) scheme in conjunction with feed-forward strategy based on the dynamic partial least squares (DyPLS) framework is proposed. Unlike the traditional methods to decouple multi-input multi-output (MIMO) systems, the DyPLS framework automatically decomposes the MIMO process into a multi-loop system in the PLS subspace in the modeling stage. The dynamic filters with identical structure are used to build the dynamic PLS model, which retains the orthogonality among the latent variables. To address the model mismatch problem, an off-line least squares method is applied to obtain a set of optimal filter parameters in each latent space. Without losing the merits of model-based control, a simple and easy-tuned IMC structure is readily carried over to the dynamic PLS control framework. In addition, by projecting the measurable disturbance into the latent subspace, a multi-loop feed-forward control is yielded to achieve better performance for disturbance rejection. Simulation results of a distillation column are used to further demonstrate this new strategy outperforms conventional control schemes in servo behavior and disturbance rejection. © 2010 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press (CIP).

@inproceedings{
 title = {Multiloop nonlinear IMC strategy design under PLS framework using ARX-neural network model},
 type = {inproceedings},
 year = {2010},
 keywords = {ARX-NN,Mismatch nonlinear IMC scheme pH neutralization pr,Model,Plant-model},
 pages = {3554-3559},
 id = {e8c838ce-9d29-3b34-bbe3-2cefd8f79d50},
 created = {2020-07-31T17:58:45.903Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.452Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {A novel multi-loop nonlinear Internal Model Control (IMC) strategy is developed for MIMO systems under the Partial Least Squares (PLS) framework, which automatically decomposes the MIMO process into several univariate systems in the latent space. The ARX-neural network (ARX-NN) model is incorporated in the PLS subspace and identified via optimizing two parameter sets so that the plant-model mismatch is minimized. The cascaded mode of ARX-neural network model facilitates the parameters estimation in the process identification, as well as nonlinear IMC design. With perfect modeling, the nonlinear closed-loop system can be reduced to IMC robust filter with a system pure delay factor under the proposed nonlinear IMC scheme. By tuning the IMC filter, the robust property of the control system is adjusted to account for the model-plant mismatch, and the offset free performance is obtained through perfectly inverting the steady-state gain of the model. The simulation result of pH neutralization process demonstrated the effectiveness of the proposed approach in disturbance rejection and tracking performance. © 2010 IEEE.},
 bibtype = {inproceedings},
 author = {Hu, Bin and Fei, Zhengshun and Zhao, Zhao and Liang, Jun},
 doi = {10.1109/WCICA.2010.5553873},
 booktitle = {Proceedings of the World Congress on Intelligent Control and Automation (WCICA)}
}

A novel multi-loop nonlinear Internal Model Control (IMC) strategy is developed for MIMO systems under the Partial Least Squares (PLS) framework, which automatically decomposes the MIMO process into several univariate systems in the latent space. The ARX-neural network (ARX-NN) model is incorporated in the PLS subspace and identified via optimizing two parameter sets so that the plant-model mismatch is minimized. The cascaded mode of ARX-neural network model facilitates the parameters estimation in the process identification, as well as nonlinear IMC design. With perfect modeling, the nonlinear closed-loop system can be reduced to IMC robust filter with a system pure delay factor under the proposed nonlinear IMC scheme. By tuning the IMC filter, the robust property of the control system is adjusted to account for the model-plant mismatch, and the offset free performance is obtained through perfectly inverting the steady-state gain of the model. The simulation result of pH neutralization process demonstrated the effectiveness of the proposed approach in disturbance rejection and tracking performance. © 2010 IEEE.

@inproceedings{
 title = {A method of fault diagnosis based on PCA and bayes classification},
 type = {inproceedings},
 year = {2010},
 keywords = {Fault diagnosis,Naive bayes classification,Principal components analysis,TE process},
 pages = {5628-5631},
 id = {5761503c-c09f-37f8-8d74-98efdad8b65b},
 created = {2020-07-31T17:58:45.926Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.092Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {By Principal Components Analysis (PCA) method, we can extract the main element from the fault sample set to obtain reduced feature space, which is suitable for fault diagnosis. Bayes method has shown its good classification performance in fault diagnosis, while the real-timing of this method can be guaranteed effectively. By taking advantages of the PCA and Naive Bayes classification, an integrated approach is proposed for the fault diagnosis of chemical process. Firstly, the dimension of industrial data was reduced by PCA method, and the resulting data were discretized to some grades for Bayes classification. The simulation results of TE process show that PCA-Bayes classification is feasible to detect and locate faults quickly with good real time property and high robustness. © 2010 IEEE.},
 bibtype = {inproceedings},
 author = {Shi, Xiangrong and Liang, Jun and Ye, Lubin and Hu, Bin},
 doi = {10.1109/WCICA.2010.5554741},
 booktitle = {Proceedings of the World Congress on Intelligent Control and Automation (WCICA)}
}

By Principal Components Analysis (PCA) method, we can extract the main element from the fault sample set to obtain reduced feature space, which is suitable for fault diagnosis. Bayes method has shown its good classification performance in fault diagnosis, while the real-timing of this method can be guaranteed effectively. By taking advantages of the PCA and Naive Bayes classification, an integrated approach is proposed for the fault diagnosis of chemical process. Firstly, the dimension of industrial data was reduced by PCA method, and the resulting data were discretized to some grades for Bayes classification. The simulation results of TE process show that PCA-Bayes classification is feasible to detect and locate faults quickly with good real time property and high robustness. © 2010 IEEE.

@article{
 title = {Soft-sensing research on the gas phase ethylene polymerization in fluidized bed reactor based on DPCA-RBF network},
 type = {article},
 year = {2010},
 keywords = {DPCA,Gas phase ethylene polymerization,RBF neural network,Soft-sensing},
 pages = {481-487},
 volume = {31},
 id = {c1628703-1587-3d6b-9d04-735077749697},
 created = {2020-07-31T17:58:46.087Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.319Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Gas phase ethylene polymerization in fluidized bed reactor is a complicated process, involving the characteristics of high dimension, nonlinear, dynamic and strong noise, and it' s hard to measure the quality variables. To solve the problem of soft-sensing of the key quality variables on line, we first use DPCA to extract the principal component variables from the process variables aiming at eliminating noise and pertinence, reveal the dynamic identity between process variables, and then use RBF modeling method to establish the network topology between principal component variables and quality variables. We adopt PCA-RBF model and DPCA-RBF model on the function data and industrial real-time data respectively, and find that the modeling method of DPCA-RBF is better than the methods of PCA-RBF and RBF when nonlinear, dynamic, noise, and pertinence exist in the modeling data. Thereby, DPCA-RBF modeling method is more suitable for the soft-sensing of industrial real-time variables.},
 bibtype = {article},
 author = {Yang, Min and Hu, Bin and Fei, Zhengshun and Zheng, Pingyou and Liang, Jun},
 journal = {Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument},
 number = {3}
}

Gas phase ethylene polymerization in fluidized bed reactor is a complicated process, involving the characteristics of high dimension, nonlinear, dynamic and strong noise, and it' s hard to measure the quality variables. To solve the problem of soft-sensing of the key quality variables on line, we first use DPCA to extract the principal component variables from the process variables aiming at eliminating noise and pertinence, reveal the dynamic identity between process variables, and then use RBF modeling method to establish the network topology between principal component variables and quality variables. We adopt PCA-RBF model and DPCA-RBF model on the function data and industrial real-time data respectively, and find that the modeling method of DPCA-RBF is better than the methods of PCA-RBF and RBF when nonlinear, dynamic, noise, and pertinence exist in the modeling data. Thereby, DPCA-RBF modeling method is more suitable for the soft-sensing of industrial real-time variables.

@article{
 title = {Optimal grade transition of polymerization process with path constraints},
 type = {article},
 year = {2010},
 keywords = {Control vector parameterization,Grade transition,Path constraints,Polymerization},
 pages = {893-900},
 volume = {61},
 id = {3bcb5f78-2a3b-3554-8402-4acd4b16477f},
 created = {2020-07-31T17:58:46.117Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:42.954Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {To meet a demand for various polymer products, grade transitions are frequently required in the polymerization process. The recent studies for grade transition optimization mostly focused on adjusting the quality specifications to target values. However, the variations on quality specifications and state variables during the grade transition will greatly affect the operation stability of the system and the product qualities. In this study, the authors proposed a simple and effective approach to alleviate the fluctuations during grade transition by adding path constraints to the optimization structure of grade transition in a gas-phase fluidized bed reactor for polyethylene. The path constraints were transformed to control variable constraints by solving the differential algebraic equation, which significantly improves the traditional control vector parameterization method to solve dynamic optimization problems with path constraints. The simulation results confirm the effectiveness of the proposed approach to enhance the operation stability. ©All Rights Reserved.},
 bibtype = {article},
 author = {Fei, Zhengshun and Hu, Bin and Ye, Lubin and Zheng, Pingyou and Liang, Jun},
 journal = {Huagong Xuebao/CIESC Journal},
 number = {4}
}

To meet a demand for various polymer products, grade transitions are frequently required in the polymerization process. The recent studies for grade transition optimization mostly focused on adjusting the quality specifications to target values. However, the variations on quality specifications and state variables during the grade transition will greatly affect the operation stability of the system and the product qualities. In this study, the authors proposed a simple and effective approach to alleviate the fluctuations during grade transition by adding path constraints to the optimization structure of grade transition in a gas-phase fluidized bed reactor for polyethylene. The path constraints were transformed to control variable constraints by solving the differential algebraic equation, which significantly improves the traditional control vector parameterization method to solve dynamic optimization problems with path constraints. The simulation results confirm the effectiveness of the proposed approach to enhance the operation stability. ©All Rights Reserved.

@article{
 title = {Multiscale classification and its application to process monitoring},
 type = {article},
 year = {2010},
 keywords = {Feature extraction,Multi-class classifier,Multiscale analysis,Process monitoring,Stationary wavelet transform},
 pages = {425-434},
 volume = {11},
 id = {d8ad4262-edcd-325e-8da4-a92322d5e30f},
 created = {2020-07-31T17:58:46.230Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.229Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Multiscale classification has potential advantages for monitoring industrial processes generally driven by events in different time and frequency domains. In this study, we adopt stationary wavelet transform for multiscale analysis and propose an applicable scale selection method to obtain the most discriminative scale features. Then using the multiscale features, we construct two classifiers: (1) a supported vector machine (SVM) classifier based on classification distance, and (2) a Bayes classifier based on probability estimation. For the SVM classifier, we use 4-fold cross-validation and grid-search to obtain the optimal parameters. For the Bayes classifier, we introduce dimension reduction techniques including kernel Fisher discriminant analysis (KFDA) and principal component analysis (PCA) to investigate their influence on classification accuracy. We tested the classifiers with two simulated benchmark processes: the continuous stirred tank reactor (CSTR) process and the Tennessee Eastman (TE) process. We also tested them on a real polypropylene production process. The performance comparison among the classifiers in different scales and scale combinations showed that when datasets present typical scale features, the multiscale classifier had higher classification accuracy than conventional single scale classifiers. We also found that dimension reduction can generally contribute to a better classification in our tests. © 2010 Zhejiang University and Springer-Verlag Berlin Heidelberg.},
 bibtype = {article},
 author = {Liu, Yu Ming and Ye, Lu Bin and Zheng, Ping You and Shi, Xiang Rong and Hu, Bin and Liang, Jun},
 doi = {10.1631/jzus.C0910430},
 journal = {Journal of Zhejiang University: Science C},
 number = {6}
}

Multiscale classification has potential advantages for monitoring industrial processes generally driven by events in different time and frequency domains. In this study, we adopt stationary wavelet transform for multiscale analysis and propose an applicable scale selection method to obtain the most discriminative scale features. Then using the multiscale features, we construct two classifiers: (1) a supported vector machine (SVM) classifier based on classification distance, and (2) a Bayes classifier based on probability estimation. For the SVM classifier, we use 4-fold cross-validation and grid-search to obtain the optimal parameters. For the Bayes classifier, we introduce dimension reduction techniques including kernel Fisher discriminant analysis (KFDA) and principal component analysis (PCA) to investigate their influence on classification accuracy. We tested the classifiers with two simulated benchmark processes: the continuous stirred tank reactor (CSTR) process and the Tennessee Eastman (TE) process. We also tested them on a real polypropylene production process. The performance comparison among the classifiers in different scales and scale combinations showed that when datasets present typical scale features, the multiscale classifier had higher classification accuracy than conventional single scale classifiers. We also found that dimension reduction can generally contribute to a better classification in our tests. © 2010 Zhejiang University and Springer-Verlag Berlin Heidelberg.

@article{
 title = {Multivariable statistical process monitoring method based on multiscale analysis},
 type = {article},
 year = {2009},
 keywords = {Discrete wavelet transform,Multiscale analysis,Principal component analysis,Statistical process monitoring},
 pages = {952-958},
 volume = {60},
 id = {b236d377-f592-3251-855a-efa37d17da88},
 created = {2020-07-31T17:58:46.180Z},
 file_attached = {false},
 profile_id = {c23b2020-6c99-31d5-8474-4a35eb1af667},
 last_modified = {2021-04-09T16:14:43.371Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The existing multiscale principal component analysis method provides an effective way to monitor industrial processes with multiscale features due to the influence of events at different time-frequency values, but there are two main shortcomings with respect to this method: a reconstruction step is needed which results in a great number of monitoring models to be constructed; and Haar wavelet is used to do a wavelet transform for multiscale analysis, but it is not continuous and therefore not good at approximating practical signal. Hence, a modified multiscale monitoring method was proposed, which not only eliminated the reconstruction step based on the analysis of scale feature of the fault but also replaced Haar wavelet with sym wavelet, which was continuous and had a higher order vanishing moment and thus was more suitable to extract multiscale features. In particular, the proposed method gave an alternative multiscale way to determine the location and duration of two typical faults: step fault and oscillating fault, and solve the problem of boundary effect and signal alignment accompanying the introduction of sym wavelet. Finally, the effectiveness of the proposed methods was verified by simulated experiments on a standard CSTR problem. © All Rights Reserved.},
 bibtype = {article},
 author = {Liu, Yuming and Liang, Jun and Hu, Bin and Ye, Lubin and Shi, Xiangrong},
 journal = {Huagong Xuebao/CIESC Journal},
 number = {4}
}

The existing multiscale principal component analysis method provides an effective way to monitor industrial processes with multiscale features due to the influence of events at different time-frequency values, but there are two main shortcomings with respect to this method: a reconstruction step is needed which results in a great number of monitoring models to be constructed; and Haar wavelet is used to do a wavelet transform for multiscale analysis, but it is not continuous and therefore not good at approximating practical signal. Hence, a modified multiscale monitoring method was proposed, which not only eliminated the reconstruction step based on the analysis of scale feature of the fault but also replaced Haar wavelet with sym wavelet, which was continuous and had a higher order vanishing moment and thus was more suitable to extract multiscale features. In particular, the proposed method gave an alternative multiscale way to determine the location and duration of two typical faults: step fault and oscillating fault, and solve the problem of boundary effect and signal alignment accompanying the introduction of sym wavelet. Finally, the effectiveness of the proposed methods was verified by simulated experiments on a standard CSTR problem. © All Rights Reserved.