Fuzzy control system

Quantum mechanics

Adaptive control

Control (management)

Engineering

Fault detection and isolation

Backstepping

Biology

Control engineering

Actuator

Adaptive system

Computer science

Bounded function

Controller (irrigation)

Physics

Nonlinear system

Mathematics

Fuzzy logic

Agronomy

Lyapunov function

Mathematical analysis

Artificial intelligence

Control theory (sociology)

IEEE Transactions on Fuzzy Systems

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.

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