Near Optimality of Linear Delayed Doubly Stochastic Control Problem | Zendy

Jie Xu | Zendy; Ruiqiang Lin | Zendy

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Near Optimality of Linear Delayed Doubly Stochastic Control Problem

Author(s) -

Jie Xu,

Ruiqiang Lin

Publication year - 2021

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2021/4487092

Subject(s) - mathematics , optimal control , stochastic control , maximum principle , regular polygon , state (computer science) , control (management) , domain (mathematical analysis) , control theory (sociology) , linear quadratic gaussian control , mathematical optimization , mathematical analysis , computer science , algorithm , geometry , artificial intelligence

In this paper, we study a kind of near optimal control problem which is described by linear quadratic doubly stochastic differential equations with time delay. We consider the near optimality for the linear delayed doubly stochastic system with convex control domain. We discuss the case that all the time delay variables are different. We give the maximum principle of near optimal control for this kind of time delay system. The necessary condition for the control to be near optimal control is deduced by Ekeland’s variational principle and some estimates on the state and the adjoint processes corresponding to the system.

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