Adaptive fuzzy decentralised fault-tolerant control for nonlinear large-scale systems with actuator failures and unmodelled dynamics

Abstract

This paper discusses the adaptive fuzzy decentralised fault-tolerant control (FTC) problem for a class of nonlinear large-scale systems in strict-feedback form. The systems under study contain the unknown nonlinearities, unmodelled dynamics, actuator faults and without the direct measurements of state variables. With the help of fuzzy logic systems identifying the unknown functions and a fuzzy adaptive observer is designed to estimate the unmeasured states. By using the backstepping design technique and the dynamic surface control approach and combining with the changing supply function technique, a fuzzy adaptive FTC scheme is developed. The main features of the proposed control approach are that it can guarantee the closed-loop system to be input–to-state practically stable, and also has the robustness to the unmodelled dynamics. Moreover, it can overcome the so-called problem of ‘explosion of complexity’ existing in the previous literature. Finally, simulation studies are provided to illustrate the effectiveness of the proposed approach.

Keywords:

• nonlinear large-scale systems
• fuzzy fault-tolerant control
• actuator faults
• unmodelled dynamic
• dynamic surface control

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 61374113], [grant number 61203008]; Liaoning Innovative Research Team in University [grant number LT2012013].

Notes on contributors

Yinyin Xu

Yinyin Xu received her BS degree in applied mathematics from Liaoning University of Technology, Jinzhou, China, in 2010. She is now working towards her ME degree in applied mathematics, from Liaoning University of Technology, Jinzhou, China. Her current research interests include nonlinear adaptive control, fuzzy control and fault-tolerant control.

Shaocheng Tong

Shaocheng Tong received his BA degree in mathematics from Jinzhou Normal College, Jinzhou, China; the MA degree in fuzzy mathematics from Dalian Marine University, Dalian, China; and the Ph.D. degree in fuzzy control from Northeastern University, Shenyang, China, in 1982, 1988 and 1997, respectively. Currently, he is a professor in the Department of Basic Mathematics, Liaoning University of Technology, Jinzhou, China. His research interests include fuzzy control theory, nonlinear adaptive control and intelligent control.

Yongming Li

Yongming Li received his BS degree and MS degree in applied mathematics from Liaoning University of Technology, Jinzhou, China, in 2004 and 2007, respectively. He is currently a lecturer in the Department of Basic Mathematics, Liaoning University of Technology. His current research interests include fuzzy and neural networks control and nonlinear adaptive control.