This paper investigates fault-tolerant tracking control problem for autonomous
underwater vehicle (AUV) with rudders faults and ocean current disturbance.
The adaptive dynamic programming (ADP) method is adopted to transform the
fault-tolerant tracking control problem into an optimal control problem. Two
neural-network estimators (NNEs) are designed to estimate rudders faults and
ocean current disturbance respectively. The estimated rudders faults and the
estimated ocean current disturbance are utilized to construct the performance
index function. By using policy iteration (PI), critic neural network and action
neural network are constructed to solve the Hamilton-Jacobi-Bellman (HJB)
equation. The error tracking system of AUV is guaranteed to be uniformly ul-
timately bounded (UUB) based on the Lyapunov stability theorem. Simulation
results are given to verify the effectiveness of the control scheme proposed in
this paper.
