HJB equations for certain singularly controlled diffusions
Abstract
Given a closed, bounded convex set W⊂ Rd with nonempty interior, we consider a control problem in which the state process W and the control process U satisfy \[Wt= w0+∫0t(Ws) ds+∫0tσ(Ws) dZs+GUt∈ W, t0,\] where Z is a standard, multi-dimensional Brownian motion, ,σ∈ C0,1(W), G is a fixed matrix, and w0∈W. The process U is locally of bounded variation and has increments in a given closed convex cone U⊂Rp. Given g∈ C(W), ∈Rp, and α>0, consider the objective that is to minimize the cost \[J(w0,U)[∫0∞e-α sg(Ws) ds+∫[0,∞)e-α s d(· Us)]\] over the admissible controls U. Both g and · u (u∈U) may take positive and negative values. This paper studies the corresponding dynamic programming equation (DPE), a second-order degenerate elliptic partial differential equation of HJB-type with a state constraint boundary condition. Under the controllability condition GU=Rd and the finiteness of H(q)=u∈U1\-Gu· q-· u\, q∈ Rd, where U1=\u∈U:|Gu|=1\, we show that the cost, that involves an improper integral, is well defined. We establish the following: (i) the value function for the control problem satisfies the DPE (in the viscosity sense), and (ii) the condition ∈fq∈RdH(q)<0 is necessary and sufficient for uniqueness of solutions to the DPE. The existence and uniqueness of solutions are shown to be connected to an intuitive ``no arbitrage'' condition. Our results apply to Brownian control problems that represent formal diffusion approximations to control problems associated with stochastic processing networks.