Adaptive dynamic programming-based multi-fault tolerant control of reconfigurable manipulator with input constraint

In this paper, a multi-fault tolerant controller considering actuator saturation is proposed. Based on the adaptive dynamic programming(ADP) algorithm, the fault tolerant control of the reconfigurable manipulator with sensor and actuator faults are carried out. Firstly, combined with the state space expression, the nonlinear transformation of sensor fault is performed by adopting the differential homeomorphism principle. An improved cost function is constructed based on the fault estimation function obtained by the fault observer, and combined with hyperbolic tangent function to deal with input constraint problem. Then, an evaluation neural network (NN) is established and the Hamilton–Jacobi–Bellman (HJB) equation is solved by online strategy iterative algorithm. Furthermore, based on Lyapunov theorem, the stability of reconfigurable manipulator systems with multi-fault are proved. Lastly, the simulation studies are used to certify the effectiveness of the presented fault tolerant control (FTC) scheme.