Optimal Control for A Class of Linear Stochastic Impulsive Systems with Partially Unknown Information

被引：0

作者：

Wu, Yan ^{[1
]}

Luo, Shixian ^{[1
]}

机构：

[1] Guangxi Univ, Sch Elect Engn, Nanning, Peoples R China

来源：

2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2023年

基金：

中国国家自然科学基金;

关键词：

optimal control; stochastic impulsive system; reinforcement learning control;

D O I：

10.1109/CCDC58219.2023.10327310

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper studies the optimal impulsive control problems of linear stochastic impulsive systems with periodic impulses and partially unknown information. By utilizing the collocation method combined with a periodic Lyapunov function, a sufficient condition for stochastic optimal impulsive control is derived in terms of a hybrid Riccati equation. Based on Bellman's dynamic programming principle, an online reinforcement learning algorithm is further presented to attain optimal impulsive control with partial system information. A numerical simulation illustrates the effectiveness of the proposed control method.

引用

页码：1768 / 1773

页数：6

共 22 条

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