Anti-saturation Fault-tolerant Control of Multi-fault Reconfigurable Manipulator System with Uncertain Environment

Abstract

An anti-saturation fault-tolerant control method based on adaptive dynamic programming (ADP) was presented for the reconfigurable manipulator with uncertain environment. Differential homeomorphism theory is used to change the system structure of nonlinear transformation, and convert nonlinearly of sensor faults of the system. The adaptive fault observer is designed to real-time detection of actuator and sensor faults, and the fault sensor signal is replaced by the output signal. The hyperbolic tangent function is used to solve the actuator saturation problem. Then, an evaluation neural network (NN) is established, and the Hamilton-Jacobi-Bellman (HJB) equation is solved by online strategy iterative algorithm, then the value of approximate optimal feedback controller can be obtained. Using Lyapunov stability theorem to assure the uniformly and ultimately bounded (UUB) of the nonlinear system. Finally, the validity of the presented optimal FTC scheme is confirmed by simulation results.