Policy iteration-based adaptive optimal control for Markov jump systems:a transition-probability-free asynchronous approach  

作　　者：Weidi CHENG Chengcheng REN Shuping HE Changyin SUN 

机构地区：[1]Key Laboratory of Intelligent Computing and Signal Processing(Ministry of Education),School of Electrical Engineering and Automation,Anhui University,Hefei 230601,China [2]Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment,School of Electrical Engineering and Automation,Anhui University,Hefei 230601,China [3]Information Materials and Intelligent Sensing Laboratory of Anhui Province,Hefei 230601,China [4]Engineering Research Center of Autonomous Unmanned System Technology(Ministry of Education),School of Artificial Intelligence,Anhui University,Hefei 230601,China

出　　处：《Science China(Information Sciences)》2024年第11期359-360,共2页中国科学（信息科学）（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.62073001);the Anhui Provincial Key Research and Development Project(Grant No.2022i01020013);the University Synergy Innovation Program of Anhui Province(Grant No.GXXT-2021-010);the Anhui Province Graduate Education Quality Project(Grant No.2023xscx027)。

摘　　要：The controller and filter design problems of Markov jump systems(MJSs)have gained significant attention over the past few decades.These studies include various aspects,including stochastic stabilization[1],optimal tracking control[2],and dissipative filter design[3].Although numerous publications address the optimal controller design for MJSs,the issue of hidden MJSs,particularly those with mismatched jumping modes between the system and the controller,has rarely been explored.

关 键 词：optimal ITERATION STABILIZATION 

分 类 号：O211.62[理学—概率论与数理统计] O232[理学—数学]