Policy Iteration for Optimal Control of Discrete-Time Time-Varying Nonlinear Systems  

作　　者：Guangyu Zhu Xiaolu Li Ranran Sun Yiyuan Yang Peng Zhang 

机构地区：[1]Beijing Research Center of Urban Traffic Information Sensing and Service Technologies [2]Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China [3]Transport Planning and Research Institute,Ministry of Transport,China,Beijing 100028,China

出　　处：《IEEE/CAA Journal of Automatica Sinica》2023年第3期781-791,共11页自动化学报（英文版）

基　　金：supported in part by Fundamental Research Funds for the Central Universities(2022JBZX024);in part by the National Natural Science Foundation of China(61872037,61273167)。

摘　　要：Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iteration(DTTV)algorithm,is developed.The iterative control law is designed to update the iterative value function which approximates the index function of optimal performance.The admissibility of the iterative control law is analyzed.The results show that the iterative value function is non-increasingly convergent to the Bellman-equation optimal solution.To implement the algorithm,neural networks are employed and a new implementation structure is established,which avoids solving the generalized Bellman equation in each iteration.Finally,the optimal control laws for torsional pendulum and inverted pendulum systems are obtained by using the DTTV policy iteration algorithm,where the mass and pendulum bar length are permitted to be time-varying parameters.The effectiveness of the developed method is illustrated by numerical results and comparisons.

关 键 词：Adaptive critic designs adaptive dynamic programming approximate dynamic programming optimal control policy iteration TIME-VARYING 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]