Network-based gain-scheduled control for preview path tracking of autonomous electric vehicles subject to communication delays

• Published in: International journal of systems science Vol. 53; no. 12; pp. 2549 - 2565
• Main Authors: Gao, Zifan, Wu, Tao, Zhang, Dawei, Zhu, Shuqian
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 10.09.2022; Taylor & Francis Ltd
• Subjects: Apexes; asynchronous gain-scheduled control; Autonomous electric vehicle; Control methods; Deviation; Electric vehicles; Mathematical models; Model accuracy; Modelling; modelling complexity; Numerical methods; Parameters; Path tracking; polytope model; preview path tracking; Scheduling; Tracking control; Tracking problem
• ISSN: 0020-7721; 1464-5319
• DOI: 10.1080/00207721.2021.2005177

The preview path tracking problem of autonomous electric vehicles with event-triggered transmission and bounded communication delays is addressed using polytope modelling and asynchronous gain-scheduled control methods. By finding a polytope with as few vertices as possible to wrap the curve composed of all time-varying parameters, a new polytope modelling method is proposed to describe the vehicle lateral dynamics, which can not only reduce the modelling complexity greatly but also keep the modelling accuracy. Based on the polytope system model, a network-based gain-scheduled controller that operates asynchronously with the polytope system is constructed, where the scheduling parameters are driven by transmitted longitudinal velocity. By computing the deviation bounds of scheduling parameters and utilising the deviation-bound-dependent method, an asynchronous gain-scheduled control design method is presented. The feasibility and advantages of the proposed methods are shown by numerical verification.