Adaptive Fuzzy Tracking Control for Uncertain Nonlinear Systems With Multiple Actuators and Sensors Faults

This article researches the adaptive fuzzy tracking control problem for uncertain nonlinear systems with multiple actuators and sensors faults. Compared with previous studies, all states of the system cannot be measured accurately in this article due to the existence of multiple sensors faults, and it brings significant difficulties to the design of the control scheme. Moreover, multiple actuators faults and external disturbance can also bring challenges to controller design. To solve these problems, we design different adaptive update laws to relieve the effects of unknown actuators faults, sensors faults, and external disturbance, respectively. Furthermore, the actual states can be estimated by combining sensors outputs with adaptive parameters. On this basis, the unknown nonlinear functions are approximated through the combining of fuzzy logic systems and the estimation of states. Then, a novel adaptive fuzzy tracking control algorithm is completed by the backstepping method. By employing the Lyapunov function, the presented novel fault-tolerant control algorithm can guarantee all signals of the system are bounded in spite of the occurrence of multiple faults. Finally, we verify the availability of the novel algorithm by comparing the control performance of the two algorithms.

Automated summary

This article investigates the problem of adaptive fuzzy tracking control for uncertain nonlinear systems with multiple actuators and sensors faults. The challenge of designing the control scheme arises from the fact that all states of the system cannot be accurately measured due to the presence of multiple sensor faults. Additionally, the design of the controller is complicated by multiple actuator faults and external disturbance. To address these issues, different adaptive update laws are designed to mitigate the effects of unknown actuator faults, sensor faults, and external disturbance. The actual states are estimated by combining sensor outputs with adaptive parameters, and the unknown nonlinear functions are approximated using a combination of fuzzy logic systems and state estimation. A novel adaptive fuzzy tracking control algorithm is then developed using the backstepping method. The proposed fault-tolerant control algorithm ensures bounded signals of the system despite the occurrence of multiple faults by employing the Lyapunov function. The effectiveness of the novel algorithm is verified by comparing its control performance to that of another algorithm.