Adaptive fuzzy asymptotic control design for MIMO nonlinear systems with state constraints

Abstract

This paper addresses the asymptotic control problem of uncertain multi-input and multi-output (MIMO) nonlinear systems. The considered MIMO systems contain unknown virtual control coefficients (UVCCs) and state constraints. A creative Lyapunov function by associating with the lower bounds of UVCCs is presented to counteract the adverse effect deriving from UVCCs. The state constraints are ensured by utilising the barrier Lyapunov function. Moreover, the asymptotic tracking controller is recursively constructed by combining the backstepping technique with fuzzy logic systems. The remarkable character of the designed controller is that the asymptotic tracking performance can be achieved by introducing some smooth functions into adaptive backstepping procedure. In contrast to the existing results, the conditions on the UVCCs are relaxed. Finally, the new control design is illustrated by a practical example.

Keywords:

• Asymptotic tracking control
• state constraints
• bound estimation method
• nonlinear systems

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China under grant numbers 52171299 and 61803116,62173103 and in part by the Fundamental Research Funds for the Central Universities of China under grant number 3072022JC0402.

Notes on contributors

Yongchao Liu

Yongchao Liu received the Ph.D. degree in control science and engineering from Harbin Engineering University, Harbin, China, in 2021. He is currently an Associate Professor with the Qingdao University. His research interests include nonlinear adaptive control, fuzzy control and neural network control for nonlinear systems.

Bowen Zeng

Bowen Zeng received the Ph.D. degree in control science and engineering from Harbin Engineering University, Harbin, China, in 2012. He is currently a Lecturer with the Harbin Engineering University. His research interests include ship motion control and embedded system design and application.

Qidan Zhu

Qidan Zhu received the Ph.D. degrees in control theory and control engineering from Harbin Engineering University, Harbin, China, in 2001. He is a Professor with the Harbin Engineering University, Harbin, China. His research interests include robot intelligent control, computer vision and intelligent control theory.

Lipeng Wang

Lipeng Wang received the Ph.D. degree in control science and engineering from Harbin Engineering University, in 2017. His research interests include nonlinear control and model predictive control.