Model predictive longitudinal control for autonomous electric vehicles with tracking differentiator

ABSTRACT

In this paper, the longitudinal control is investigated for an autonomous electric vehicle with a tracking differentiator. The autonomous electric vehicle is modelled as a longitudinal system for model predictive control. The tracking differentiator is proposed to obtain the transition profile and acceleration information. A dual-mode model predictive controller is designed for the longitudinal system to find the optimal control input, which is restricted with some constraints on the desired acceleration and its increment. Both iterative feasibility and its stability issues are analysed for the longitudinal system under the dual-mode model predictive controller. Experimental results are given to show the effectiveness of the proposed strategy.

Keywords:

• Autonomous electric vehicles (AEVs)
• longitudinal control
• model predictive control (MPC)
• tracking differentiator (TD)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 61773281, 61673292 and 61933014].

Notes on contributors

Yijing Wang

Yijing Wang received her M.S. degree in control theory and control engineering from Yanshan University and the Ph.D. degree in control theory from Peking University, China, in 2000 and 2004, respectively. In 2004, she joined the School of Electrical and Information Engineering, Tianjin University, where she is a full professor. Her research interests are intelligent vehicles, analysis and control of switched/hybrid systems and robust control.

Shizhuo Cao

Shizhuo Cao received his bachelor degree in automation from Tianjin University in 2018. Now, he is a graduate student in the School of Electrical and Information Engineering, Tianjin University. His research interests are vehicle control and trajectory tracking of autonomous vehicles.

Hongjiu Yang

Hongjiu Yang received the B.S. degree in mathematics and applied mathematics and the M.S. degree in applied mathematics from Hebei University of Science and Technology, Shijiazhuang, China, in 2005 and 2008, respectively. He received the Ph.D. degree in control science and engineering in Beijing Institute of Technology, Beijing, China. He was an Associate Professor with the Department of Automation, Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China, in 2013 and 2018. He is currently a professor with the Department of Automation, School of Electrical and Information Engineering, Tianjin University, China. His main research interests include robust control/filter theory, delta operator systems, networked control systems and active disturbance rejection control.

Zhiqiang Zuo

Zhiqiang Zuo received the M.S. degree in control theory and control engineering in 2001 from Yanshan University and the Ph.D. degree in control theory in 2004 from Peking University, China. In 2004, he joined the School of Electrical and Information Engineering, Tianjin University, where he is a full professor. From 2008 to 2010, he was a Research Fellow in the Department of Mathematics, City University of Hong Kong. From 2013 to 2014, he was a visiting scholar at the University of California, Riverside. His research interests include intelligent vehicles, nonlinear control, robust control and multi-agent systems with application to intelligent vehicles.

Li Wang

Li Wang received the B.S. and M.S. degrees in detection technology and automation devices from Yanshan University in 1999 and 2002, respectively, and the Ph.D. degree in precision instruments and machinery from Beihang University in 2004. From 2004 to 2006, he was a Post-Doctoral Researcher with Beihang University. He is currently Dean of the School of Electrical and Control Engineering, North China University of Technology University. His research interests include intelligent traffic signal control and traffic simulation, Internet of Vehicles and artificial intelligence.

Xiaoyuan Luo

Xiaoyuan Luo received the Ph.D. degree in control theory and control engineering from Yanshan University, Qinhuangdao, China, in 2005. He is currently a professor with the School of Electrical Engineering, Yanshan University. His current research interests include formation of unmanned vehicles, cooperative control of multi-agent systems and wireless sensor networks.