Distributed low-complexity output feedback tracking control for nonlinear multi-agent systems with unmodeled dynamics and prescribed performance

ABSTRACT

This paper investigates the prescribed performance distributed output consensus problem under directed graphs. With the utilisation of a filter, the original system of each follower can be converted into a strict-feedback system. Then, we design a prescribed performance output feedback distributed control protocol by applying the backstepping approach in the converted system. The proposed protocol can guarantee that the consensus tracking error of each agent evolves in predefined decaying bounds to achieve the prescribed performance, that is, the consensus tracking error of each agent converges to a predetermined residual set at a convergence rate no less than a prespecified value and exhibiting a maximum overshoot less than a preassigned constant. Moreover, during the process of consensus, all the signals in the closed-loop system are globally uniformly bounded. A simulation example is given to verify the effectiveness of the proposed control protocol.

Keywords:

• Distributed control
• output feedback
• unmodeled dynamics
• directed graph
• low-complexity control
• prescribed performance

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Xuan Cai http://orcid.org/0000-0001-9040-8912

Gang Wang http://orcid.org/0000-0001-7831-5246

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 61374040, 61673277, 61503262].

Notes on contributors

Xuan Cai

Xuan Cai was born in Shanghai, China, in 1990. He received the M.E. degree from the University of Shanghai for Science and Technology, Shanghai, China in 2015 and is currently pursuing the Ph.D. degree in control science and engineering at the University of Shanghai for Science and Technology, Shanghai, China. His current research interests include nonlinear control theory, distributed control of nonlinear systems and adaptive control.

Chaoli Wang

Chaoli Wang received the B.S. and M.Sc. degrees from Mathematics Department, Lanzhou University, Lanzhou, China, in 1986 and 1992, respectively, and the Ph.D. degree in control theory and engineering from the Beijing University of Aeronautics and Astronautics, Beijing, China, in 1999. He is a Professor with the School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China. From 1999 to 2000, he was a Post-Doctoral Research Fellow with the Robotics Laboratory of Chinese Academy of Sciences, Shenyang, China. From 2001 to 2002, he was a Research Associate with the Department of Automation and Computer-Aided Engineering, the Chinese University of Hong Kong, Hong Kong. Since 2003, he has been with the Department of Electrical Engineering, University of Shanghai for Science and Technology, Shanghai, China. His current research interests include nonlinear control, robust control, robot dynamic and control, visual servoing feedback control, and pattern identification.

Gang Wang

Gang Wang was born in Chifeng, China, in 1990. He received the B.Sc. degree in Information and Computing Science and the Ph.D. degree in Systems Analysis and Integration from the University of Shanghai for Science and Technology, Shanghai, China, in 2012 and 2017, respectively. He is currently a Research Associate in the Department of Electrical and Biomedical Engineering, University of Nevada, Reno. His research interests include distributed control of nonlinear systems, adaptive control, and robotics.

Yu Li

Yu Li received the M.E. degree from the University of Shanghai for Science and Technology, Shanghai, China in 2017 and is currently pursuing the Ph.D. degree in control science and engineering at the University of Shanghai for Science and Technology, Shanghai, China. His current research interests include nonlinear control theory, distributed control of multi-agent systems, quantised and adaptive control.

Luyan Xu

Luyan Xu was born in Xinyang, China, in 1994. She received the B.Sc. degree in Henan Normal University in 2016. She is currently pursuing the Ph.D. degree in control science and engineering at the University of Shanghai for Science and Technology, Shanghai, China. Her research interests include distributed control of nonlinear systems, adaptive control, and multi-agent systems.

Zhihua Zhang

Zhihua Zhang was born in Nantong, China, in 1983.He received the M.E. degree from the University of Shanghai for Science and Technology, Shanghai, China in 2010 and is currently pursuing the Ph.D. degree in control science and engineering at the University of Shanghai for Science and Technology, Shanghai, China. He is currently with Nantong Shipping College as a lecturer. His current research interests include nonlinear control theory, distributed control of nonlinear systems and adaptive control, and robotics.