Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems

This paper is concerned with a new discrete-time policy iteration adaptive dynamic programming (ADP) method for solving the infinite horizon optimal control problem of nonlinear systems. The idea is to use an iterative ADP technique to obtain the iterative control law, which optimizes the iterative performance index function. The main contribution of this paper is to analyze the convergence and stability properties of policy iteration method for discrete-time nonlinear systems for the first time. It shows that the iterative performance index function is nonincreasingly convergent to the optimal solution of the Hamilton-Jacobi-Bellman equation. It is also proven that any of the iterative control laws can…

• NN
  National Natural Science Foundation of China

  Awards: 61374105, 61034002, 61273140, 61233001
• NS
  Natural Science Foundation of Beijing Municipality

  Award: 4132078