1. Approximate Optimal tracking Control for Nonlinear Discrete-time Switched Systems via Approximate Dynamic Programming
- Author
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Jishi Zhang, Yabin Yang, Huang Yizhe, Chunbin Qin, and Xianxing Liu
- Subjects
0209 industrial biotechnology ,Artificial neural network ,Computer science ,Hamilton–Jacobi–Bellman equation ,02 engineering and technology ,Function (mathematics) ,Tracking (particle physics) ,Tracking error ,Dynamic programming ,Nonlinear system ,020901 industrial engineering & automation ,Discrete time and continuous time ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing - Abstract
In this paper, an iterative approximate dynamic programming algorithm is proposed for solving the approximate optimal tracking control problem for a class of nonlinear discrete-time switched systems. Firstly, the optimal tracking problem is converted into designing an optimal regulator for the tracking error dynamics. And then, the iterative approximate dynamic programming algorithm is proposed to obtain the approximate solution of the Hamilton-Jacobi-Bellman (HJB) equation. Next, two neural networks are used to approximate the iterative cost function and the iterative control law, respectively. Finally, simulation results are given to verify the effectiveness of the proposed algorithm.
- Published
- 2019