Toward a cyber-physical quadrotor: Characterizing trajectory following performance. Shankar, A., Doebbeling, S., & Bradley, J. In 2017 International Conference on Unmanned Aircraft Systems (ICUAS), pages 133–142, Miami, FL, June, 2017. 2017 International Conference on Unmanned Aircraft Systems (ICUAS). doi abstract bibtex An Unmanned Aircraft System (UAS) is a CyberPhysical System (CPS) in which a host of real-time computational tasks contending for shared resources must be cooperatively managed to provide actuation input for control of the locomotion necessary to obtain mission objectives. Traditionally, control of the UAS is designed assuming a fixed, high sampling rate in order to maintain reliable performance and margins of stability. But emerging methods challenge this design by dynamically allocating resources to computational tasks, thereby affecting control and mission performance. To apply these emerging strategies, a characterization and understanding of the effects of timing on control and trajectory following performance is required. Going beyond traditional control evaluation techniques, in this paper, we characterize the trajectory following performance, timing, and control of a quadrotor UAS under discrete linear quadratic regulator control designed at various sampling rates. We develop a direct relationship between trajectory following performance and the real-time task period (i.e. sampling rate) of the real-time control task allowing future designs to trade off UAS performance and cyber resources at the planning and/or guidance layer. We also introduce new metrics for characterizing cyber-physical quadrotor performance, and lay the groundwork for the application of CPS control methods to quadrotor UASs.
@inproceedings{shankar2017cyberphysical,
address = {Miami, FL},
title = {Toward a cyber-physical quadrotor: {Characterizing} trajectory following performance},
shorttitle = {Toward a cyber-physical quadrotor},
doi = {10.1109/ICUAS.2017.7991394},
abstract = {An Unmanned Aircraft System (UAS) is a CyberPhysical System (CPS) in which a host of real-time computational tasks contending for shared resources must be cooperatively managed to provide actuation input for control of the locomotion necessary to obtain mission objectives. Traditionally, control of the UAS is designed assuming a fixed, high sampling rate in order to maintain reliable performance and margins of stability. But emerging methods challenge this design by dynamically allocating resources to computational tasks, thereby affecting control and mission performance. To apply these emerging strategies, a characterization and understanding of the effects of timing on control and trajectory following performance is required. Going beyond traditional control evaluation techniques, in this paper, we characterize the trajectory following performance, timing, and control of a quadrotor UAS under discrete linear quadratic regulator control designed at various sampling rates. We develop a direct relationship between trajectory following performance and the real-time task period (i.e. sampling rate) of the real-time control task allowing future designs to trade off UAS performance and cyber resources at the planning and/or guidance layer. We also introduce new metrics for characterizing cyber-physical quadrotor performance, and lay the groundwork for the application of CPS control methods to quadrotor UASs.},
booktitle = {2017 {International} {Conference} on {Unmanned} {Aircraft} {Systems} ({ICUAS})},
publisher = {2017 International Conference on Unmanned Aircraft Systems (ICUAS)},
author = {Shankar, A. and Doebbeling, S. and Bradley, J.},
month = jun,
year = {2017},
keywords = {Computer architecture, NSF 1638099, Planning, Real-time systems, Software, Timing, Trajectory, UAS control, autonomous aerial vehicles, control evaluation techniques, control performance, cyber-physical quadrotor, cyber-physical system, discrete linear quadratic regulator control, discrete systems, guidance layer, helicopters, linear quadratic control, mission performance, path planning, planning layer, sampling rates, stability, stability margin, trajectory control, trajectory following performance, unmanned aircraft system},
pages = {133--142},
}
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