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Optimistic Value Model of Indefinite LQ Optimal Control for Discrete‐Time Uncertain Systems
Author(s) -
Chen Yuefen,
Zhu Yuanguo
Publication year - 2018
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1591
Subject(s) - bellman equation , weighting , mathematics , optimal control , dynamic programming , discrete time and continuous time , mathematical optimization , state (computer science) , function (biology) , control theory (sociology) , quadratic equation , control (management) , value (mathematics) , computer science , algorithm , medicine , statistics , geometry , evolutionary biology , artificial intelligence , biology , radiology
Uncertainty theory is a branch of mathematics which provides a new tool to deal with the human uncertainty. Based on uncertainty theory, this paper proposes an optimistic value model of discrete‐time linear quadratic (LQ) optimal control, whereas the state and control weighting matrices in the cost function are indefinite, the system dynamics are disturbed by uncertain noises. With the aid of the Bellman's principle of optimality in dynamic programming, we first present a recurrence equation. Then, a necessary condition for the state feedback control of the indefinite LQ problem is derived by using the recurrence equation. Moreover, a sufficient condition of well‐posedness for the indefinite LQ optimal control is given. Finally, a numerical example is presented by using the obtained results.