Study on Indefinite Stochastic Linear Quadratic Optimal Control with Inequality Constraint | Zendy

Guiling Li | Zendy; Weihai Zhang | Zendy

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Study on Indefinite Stochastic Linear Quadratic Optimal Control with Inequality Constraint

Author(s) -

Guiling Li,

Weihai Zhang

Publication year - 2013

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2013/805829

Subject(s) - karush–kuhn–tucker conditions , mathematics , constraint (computer aided design) , state (computer science) , type (biology) , quadratic equation , mathematical optimization , riccati equation , stochastic control , optimal control , mathematical analysis , algorithm , ecology , geometry , biology , differential equation

This paper studies the indefinite stochastic linear quadratic (LQ) optimal control problem with an inequality constraintfor the terminal state. Firstly, we prove a generalized Karush-Kuhn-Tucker (KKT) theorem under hybrid constraints. Secondly, a new type of generalized Riccati equations is obtained, based on which a necessary condition (it is also a sufficient condition under stronger assumptions) for the existence of an optimal linear state feedback control is given by means of KKT theorem. Finally, we design a dynamic programming algorithm to solve the constrained indefinite stochastic LQ issue

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