Discrete-time distributed state feedback control for multi-robot systems. Marino, A. & Pierri, F. 2016.
Discrete-time distributed state feedback control for multi-robot systems [link]Paper  doi  abstract   bibtex   
In this paper, a general framework to control in a distributed way a system composed by multiple robots is proposed. Each robot is characterized by a discrete-time linear dynamics, and the whole system is controlled via a linear static feedback law with a feed-forward term. Usually, this form of the global control input requires a central unit or an all-to-all communication for computing the local control input of each robot. To counteract the lack of a central unit, each robot estimates, via a local observer, the overall state of the team, and such an estimate is used to compute its local control input as in the case a central unit was present. Two simulations case studies are provided in the framework of multi-robot optimal control and formation control.
@conference{
	11580_71254,
	author = {Marino, Alessandro and Pierri, Francesco},
	title = {Discrete-time distributed state feedback control for multi-robot systems},
	year = {2016},
	publisher = {Institute of Electrical and Electronics Engineers Inc.},
	volume = {2016-},
	booktitle = {Proceedings - IEEE International Conference on Robotics and Automation},
	abstract = {In this paper, a general framework to control in a distributed way a system composed by multiple robots is proposed. Each robot is characterized by a discrete-time linear dynamics, and the whole system is controlled via a linear static feedback law with a feed-forward term. Usually, this form of the global control input requires a central unit or an all-to-all communication for computing the local control input of each robot. To counteract the lack of a central unit, each robot estimates, via a local observer, the overall state of the team, and such an estimate is used to compute its local control input as in the case a central unit was present. Two simulations case studies are provided in the framework of multi-robot optimal control and formation control.},
	keywords = {Software; Artificial Intelligence; Control and Systems Engineering; Electrical and Electronic Engineering},
	url = {http://ieeexplore.ieee.org/document/7487746/},
	doi = {10.1109/ICRA.2016.7487746},
	isbn = {9781467380263},	
	pages = {5350--5355}
}

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