Abstract
In this paper, an optimal active fault tolerant control (FTC) method is presented for reconfigurable manipulator with actuator saturation based on the adaptive dynamic programming (ADP) approach. First, the saturation constraints of the manipulator systems are tackled by using hyperbolic tangent functions. Second, an actuator fault function, which is estimated via a fault observer, is used to construct the performance index function. Then, the solution of Hamiltonian-Jacobi-Bellman (HJB) equation is solved by using ADP and policy iteration (PI) methods, and the optimal performance index function is approximated by establishing a critic neural network (NN). Based on the Lyapunov theory, the closed-loop manipulator system is proved to be asymptotic stable under the optimal FTC system. Finally, simulation results are demonstrated the validity of the proposed scheme.
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