文献类型：期刊文献

中文题名：Policy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal Control

作者：Hao Zhang[1];Yan Li[1];Zhuping Wang[1];Yi Ding[1];Huaicheng Yan[2]

机构：[1]the Department of Control Science and Engineering,Tongji University,Shanghai 200092,China;[2]the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education,School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China

年份：2024

卷号：11

期号：4

起止页码：1060

中文期刊名：IEEE/CAA Journal of Automatica Sinica

外文期刊名：自动化学报（英文版）

收录：CSTPCD;;Scopus;CSCD:【CSCD2023_2024】；

基金：the National Natural Science Foundation of China(61922063,62273255,62150026);in part by the Shanghai International Science and Technology Cooperation Project(21550760900,22510712000);the Shanghai Municipal Science and Technology Major Project(2021SHZDZX0100);the Fundamental Research Funds for the Central Universities。

语种：英文

中文关键词：policy;gradient;Optimal;

摘要：Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is used to evaluate the policy.In the policy improvement process,the policy gradient based method is employed.