Nonlinear trajectory-tracking control for autonomous underwater vehicle based on iterative adaptive dynamic programming

Abstract

In this paper, an iterative adaptive dynamic programming algorithm is proposed to deal with the optimal trajectory-tracking control problems for autonomous underwater vehicle. Two iteration procedures are used in the method, which are the i-iteration and the j-iteration.The i-iteration aims to obtain iterative trajectory-tracking control laws and the j-iteration aims to obtain iterative value functions in the i-iteration. The optimal tracking control problem is converted into an optimal regulation problem by system transformation. Then the optimal regulation problem is solved by the policy iteration adaptive dynamic programming algorithm. The policy iteration algorithm is the interacting policy and value iteration algorithms. The neural networks are used to realize the proposed algorithm and the convergence and optimality properties of the proposed algorithm are analysed. Finally, simulation example is given to show the performance of the iterative adaptive dynamic programming algorithm.

Keywords

adaptive dynamic programming autonomous underwater vehicle discrete-time neural network trajectory-tracking control

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