Platooning, or controlled management of vehicle formation, enables multiple vehicles equipped with adaptive cruise control (ACC) systems to drive behind one another with a specified inter-vehicle distance, acting together as one unit. Typically, delays in throttle and brake response, as well as in vehicle computer systems, are unpredictable and time-varying, and can ultimately lead to performance degradation and system destabilization. The platoon control system must thus be designed in a way so as to mitigate the effects delays can impose on system stability. This paper presents a novel robust multi-vehicle platoon control algorithm that compensates for time-varying delays under the integral quadratic constraint (IQC) framework. All vehicle models are assumed to incorporate heterogeneous time-varying actuation/input delays. The simulation results exemplify the controller’s effectiveness in maintaining overall stability and platooning performance in the presence of time-varying input delays.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5827-1
PROCEEDINGS PAPER
Multi-Vehicle Platoon Control With Time-Varying Input Delays
Keely Varada,
Keely Varada
University of Rhode Island, Kingston, RI
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Chengzhi Yuan,
Chengzhi Yuan
University of Rhode Island, Kingston, RI
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Manbir Sodhi
Manbir Sodhi
University of Rhode Island, Kingston, RI
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Keely Varada
University of Rhode Island, Kingston, RI
Chengzhi Yuan
University of Rhode Island, Kingston, RI
Manbir Sodhi
University of Rhode Island, Kingston, RI
Paper No:
DSCC2017-5123, V001T45A004; 9 pages
Published Online:
November 14, 2017
Citation
Varada, K, Yuan, C, & Sodhi, M. "Multi-Vehicle Platoon Control With Time-Varying Input Delays." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 1: Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems. Tysons, Virginia, USA. October 11–13, 2017. V001T45A004. ASME. https://doi.org/10.1115/DSCC2017-5123
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