Adaptive Controller Design for Switched Stochastic Nonlinear Systems Subject to Unknown Dead-zone Input via New Type of Network Approach

• Published in: International journal of control, automation, and systems Vol. 21; no. 2; pp. 499 - 507
• Main Authors: He, Wen-Jing, Zhu, Shan-Liang, Li, Na, Han, Yu-Qun
• Format: Journal Article
• Language: English
• Published: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.02.2023; Springer Nature B.V; 제어·로봇·시스템학회
• Subjects: Adaptive control; Characteristic functions; Closed loops; Control; Control methods; Control systems design; Controllers; Engineering; Feedback control; Liapunov functions; Mechatronics; Nonlinear systems; Nonlinearity; Reference signals; Regular Papers; Robotics; Stochastic systems; Tracking control; 제어계측공학; multi-dimensional Taylor network; dead-zone input; Adaptive control; stochastic nonlinear systems; switched nonlinear systems
• ISSN: 1598-6446; 2005-4092
• DOI: 10.1007/s12555-021-0860-z

In this article, adaptive tracking control for a class of switched stochastic nonlinear systems subject to unknown dead-zone input using multi-dimensional Taylor network (MTN) is studied. Firstly, the characteristic function is introduced to convert the nonlinearity of the input dead-zone into a linear model. Secondly, a novel adaptive control method based on the backstepping recursive design technique is proposed, which combines MTN and common Lyapunov functions (CLFs). Significantly, a method to reduce the computational complexity of switched stochastic nonlinear systems is proposed for the first time, which introduces characteristic function and MTN technology. The result makes clear that the proposed controller can ensure all signals of the closed-loop system are bounded in probability, and the output of the system can track reference signal well. Finally, the effectiveness of proposed control method is verified by simulation results.