Observer-based adaptive fuzzy tracking control for a class of MIMO nonlinear systems with unknown dead zones and time-varying delays

ABSTRACT

The adaptive tracking control strategy is investigated for a class of multi-input and multi-output pure-feedback nonlinear delayed systems with unknown dead-zone inputs. This problem is challenging due to the existence of unknown dead zones, time-varying delays and unavoidable state variables. By constructing fuzzy approximators and state observers, the difficulties from unknown nonlinearities and unavailable state variables are surmounted, respectively. Lyapunov–Krasovskii functions are introduced to deal with the time-varying delays. The adaptive controllers are designed by a backstepping method and adaptive technique so that the closed-loop systems remain stable and the target signals can be tracked within a small error as well. At last, two examples are provided to show the effectiveness of the proposed scheme.

KEYWORDS:

• Fuzzy logic
• backstepping control
• nonlinear systems
• time-delay systems
• output feedback
• unknown dead zone

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant Nos 61673227 and 61873137.

Notes on contributors

Honghong Wang

Honghong Wang received her B.S. degree and M.S. degree at Shandong University in 2001 and 2004 respectively, and the Ph.D. degree in the Institute of Complexity Science from Qingdao University in 2018. Currently she is a Teacher of QingDao University, Qingdao, PR China. Her current research interests are mainly in systems analysis and control, neural networks and fuzzy control theory.

Bing Chen

Bing Chen received the B.A. degree in mathematics from Liaoning University, Liaoning, China, the M.A. degree in mathematics from the Harbin Institute of Technology, Heilongjiang, China, and the Ph.D. degree in electrical engineering from Northeastern University, Shenyang, China, in 1982, 1991, and 1998, respectively. He is currently a Professor with the Institute of Complexity Science, Qingdao University, Qingdao, China. His current research interests include nonlinear control systems, robust control, and adaptive fuzzy control.

Chong Lin

Chong Lin received the B.Sc. and M.Sc. degrees in applied mathematics from Northeastern University, Shenyang, China, in 1989 and 1992, respectively, and the Ph.D. degree in electrical and electronic engineering from Nanyang Technological University, Singapore, in 1999. He was a Research Associate with the Department of Mechanical Engineering, University of Hong Kong, Hong Kong, in 1999. From 2000 to 2006, he was a Research Fellow with the Department of Electrical and Computer Engineering, National University of Singapore, Singapore. Since 2006, he has been a Professor with the Institute of Complexity Science, Qingdao University, Qingdao, China. He has published more than 60 research papers and co-authored two monographs. His current research interests include systems analysis and control, robust control, and fuzzy control.

Yumei Sun

Yumei Sun received the B.Sc. degree in mathematics from Shangdong University, Jinan, China, in 2002, the M. Sc. degree in mathematics from Sun Yat-sen University, Guangzhou, China, in 2005 and Ph.D. degree in the Institute of Complexity Science from Qingdao University in 2018. Her current research interests include adaptive fuzzy control, and stochastic nonlinear systems.