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Necessary and Sufficient Near‐Optimal Conditions for Mean‐Field Singular Stochastic Controls
Author(s) -
Li Ruijing,
Liu Bin
Publication year - 2015
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.954
Subject(s) - mathematics , optimal control , regular polygon , stochastic control , domain (mathematical analysis) , field (mathematics) , mean field theory , maximum principle , state (computer science) , mathematical optimization , control (management) , control theory (sociology) , mathematical analysis , computer science , pure mathematics , algorithm , physics , geometry , quantum mechanics , artificial intelligence
We consider the near‐optimal control problems for mean‐field singular stochastic systems, where the control domain is non‐convex. By virtue of Ekeland's principle and some estimates on the state and adjoint processes, necessary and sufficient conditions for near‐optimality are established in the mean‐field framework. As an application, an example is presented to demonstrate the results.