随机控制
控制理论(社会学)
代数Riccati方程
路径(计算)
线性系统
李雅普诺夫函数
随机过程
指数稳定性
数学
Riccati方程
线性二次高斯控制
控制系统
代数数
控制(管理)
计算机科学
最优控制
数学优化
非线性系统
微分方程
工程类
数学分析
物理
人工智能
电气工程
统计
程序设计语言
量子力学
作者
Ruizhe Yu,Xiaofeng Zong
标识
DOI:10.1109/icps58381.2023.10128019
摘要
This paper aims to investigate the stabilization problem of stochastic linear system via path-dependent state-feedback control. For the given stochastic linear system, a novel feedback control is designed with the path-dependent information of the system states, and the control gains are determined by the stochastic algebraic Riccati equation. To prove that path-dependent control can drive the stochastic linear system to be exponentially stable, a novel Lyapunov function is proposed. Combined with the general theory on stability of stochastic system, it is shown that stochastic system will be stabilized in mean-square via path-dependent control.
科研通智能强力驱动
Strongly Powered by AbleSci AI