Adaptive Fuzzy Fault-Tolerant Control for Markov Jump Systems With Additive and Multiplicative Actuator Faults
Hongyan Yang, Yuchen Jiang, Shen Yin
Abstract
This article proposes a fault-tolerant compensation control approach against nonlinearity, simultaneous additive, and multiplicative actuator faults in Markov jump systems. In this article, we first exploit the fuzzy logic system (FLS) to approximate the nonlinear functions, which have no available knowledge. Then, by utilizing the adaptive backstepping technique, a FLS-based adaptive fault-tolerant compensation controller is proposed, which can completely compensate for the adverse effects, arising from the additive actuator faults, the multiplicative actuator faults, and the mismatched nonlinearity simultaneously. The stability of the closed-loop system can be guaranteed by the proposed FLS-based adaptive controller with the adaptation laws. The novelty of this article lies in the fact that the additive and multiplicative actuator faults, and mismatched nonlinearity are considered simultaneously. Besides, the renown sliding mode control approach has limitations to deal with the FTC problem considered in this article because the considered nonlinearity is a mismatched one. The proposed control approach can cope with the challenging case. Finally, a practical wheeled mobile manipulator system is used to demonstrate the effectiveness and validity of the proposed approach.