Regular Papers

International Journal of Control, Automation and Systems 2023; 21(2): 499-507

Published online January 30, 2023

https://doi.org/10.1007/s12555-021-0860-z

© The International Journal of Control, Automation, and Systems

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

Wen-Jing He, Shan-Liang Zhu, Na Li, and Yu-Qun Han*

Qingdao University of Science and Technology

Abstract

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.

Keywords Adaptive control, dead-zone input, multi-dimensional Taylor network, stochastic nonlinear systems, switched nonlinear systems.

Article

Regular Papers

International Journal of Control, Automation and Systems 2023; 21(2): 499-507

Published online February 1, 2023 https://doi.org/10.1007/s12555-021-0860-z

Copyright © The International Journal of Control, Automation, and Systems.

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

Wen-Jing He, Shan-Liang Zhu, Na Li, and Yu-Qun Han*

Qingdao University of Science and Technology

Abstract

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.

Keywords: Adaptive control, dead-zone input, multi-dimensional Taylor network, stochastic nonlinear systems, switched nonlinear systems.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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