Optimal Control of Unknown Discrete-Time Linear Systems with Additive Noise

作     者：YANG Xue LIU Shujun YANG Xue;LIU Shujun

作者机构：School of MathematicsSichuan UniversityChengdu 610064China 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2023年第36卷第2期

页      面：591-612页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 071101[理学-系统理论] 0811[工学-控制科学与工程] 0701[理学-数学] 

基　　金：supported by the National Natural Science Foundation of China under Grant No.61673284 the Science Development Project of Sichuan University under Grant No.2020SCUNL201 

主　　题：Discrete-time linear systems optimal control stochastic adaptive dynamic programming 

摘      要：The optimal control problem with a long run average cost is investigated for unknown linear discrete-time systems with additive *** authors propose a value iteration-based stochastic adaptive dynamic programming(VI-based SADP)algorithm,based on which the optimal controller is *** from the existing relevant work,the algorithm does not need to estimate the expectation(conditional expectation)and variance(conditional variance)of states or other relevant variables,and the convergence of the algorithm can be proved rigorously.A simulation example is given to verify the effectiveness of the proposed approach.