Control theory for stochastic distributed parameter systems, an engineering perspective

被引:10
|
作者
Lu, Qi [1 ]
Zhang, Xu [1 ]
机构
[1] Sichuan Univ, Sch Math, Chengdu 610064, Sichuan, Peoples R China
关键词
Stochastic distributed parameter system; Controllability; Optimal control; Pontryagin-type maximum principle; Stochastic linear quadratic problem; PARTIAL-DIFFERENTIAL-EQUATIONS; MAXIMUM PRINCIPLE; EXACT CONTROLLABILITY; NULL CONTROLLABILITY; UNIQUE CONTINUATION; EVOLUTION-EQUATIONS; PARABOLIC EQUATIONS; WELL-POSEDNESS; APPROXIMATE CONTROLLABILITY; RICCATI-EQUATIONS;
D O I
10.1016/j.arcontrol.2021.04.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The main purpose of this paper is to survey some recent progresses on control theory for stochastic distributed parameter systems, i.e., systems governed by stochastic differential equations in infinite dimensions, typically by stochastic partial differential equations. We will explain the new phenomenon and difficulties in the study of controllability and optimal control problems for one dimensional stochastic parabolic equations and stochastic hyperbolic equations. In particular, we shall see that both the formulation of corresponding stochastic control problems and the tools to solve them may differ considerably from their deterministic/finite-dimensional counterparts. More importantly, one has to develop new tools, say, the stochastic transposition method introduced in our previous works, to solve some problems in this field. The main purpose of this paper is to survey some recent progresses on control theory for stochastic distributed parameter systems, i.e., systems governed by stochastic differential equations in infinite dimensions, typically by stochastic partial differential equations. We will explain the new phenomenon and difficulties in the study of controllability and optimal control problems for one dimensional stochastic parabolic equations and stochastic hyperbolic equations. In particular, we shall see that both the formulation of corresponding stochastic control problems and the tools to solve them may differ considerably from their deterministic/finite-dimensional counterparts. More importantly, one has to develop new tools, say, the stochastic transposition method introduced in our previous works, to solve some problems in this field.
引用
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页码:268 / 330
页数:63
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