Linear quadratic stochastic optimal control with state- and control-dependent noises: A deterministic data approach

被引:3
|
作者
Zhang, Heng [1 ]
Yan, Zhiguo [2 ]
机构
[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China
[2] Qilu Univ Technol, Shandong Acad Sci, Sch Informat & Automat, Jinan 250353, Peoples R China
基金
国家重点研发计划;
关键词
Linear quadratic; Stochastic optimal control; State-and control-dependent noises; Adaptive dynamic programming; SYSTEMS; STABILIZATION; STABILIZABILITY; STABILITY;
D O I
10.1016/j.neucom.2024.127269
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper investigates an infinite -horizon linear quadratic stochastic optimal control (LQSOC) problem with state- and control -dependent noises, in which two system matrices are unknown. First, a deterministic system is introduced and a relationship among its system trajectory, its control and the matrices to be solved is formulated. Subsequently, based on the deterministic system, an adaptive dynamic programming (ADP) algorithm is established to tackle the LQSOC problem. Then, the convergence analysis is presented by proving the equivalence between the proposed algorithm and an existing policy iteration algorithm. Finally, the effectiveness of the obtained algorithm is verified by a perturbed turbocharged diesel engine optimal control design example.
引用
收藏
页数:7
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