On partially observed optimal singular control of McKean-Vlasov stochastic systems: Maximum principle approach

Abstract

In this paper we study partially observed optimal stochastic singular control problems of general Mckean-Vlasov type with correlated noises between the system and the observation. The control variable has two components the first being absolutely continuous and the second is a bounded variation nondecreasing continuous on the right with left limits. The dynamic system is governed by Ito-type controlled stochastic differential equation. The coefficients of the dynamic depend on the state process and of its probability law and the continuous control variable. In terms of a classical convex variational techniques we establish a set of necessary conditions of optimal singular control in the form of maximum principle. Our main result is proved by applying Girsanov's theorem and the derivatives with respect to probability law in Lions' sense. To illustrate our theoretical result we study partially observed linear-quadratic singular control problem of McKean-Vlasov type.