Generalized Hamilton-Jacobi-Bellman equations with Dirichlet boundary and stochastic exit time optimal control problem

preprint2015arXivOpen access

Abstract

We consider a kind of stochastic exit time optimal control problems, in which the cost function is defined through a nonlinear backward stochastic differential equation. We study the regularity of the value function for such a control problem. Then extending Peng's backward semigroup method, we show the dynamic programming principle. Moreover, we prove that the value function is a viscosity solution to the following generalized Hamilton-Jacobi-Bellman equation with Dirichlet boundary: \[ \left\{ \begin{array} [c]{l} \inf\limits_{v\in V}\left\{\mathcal{L}(x,v)u(x)+f(x,u(x),\nabla u(x) σ(x,v),v)\right\}=0, \quad x\in D,\medskip\\ u(x)=g(x),\quad x\in \partial D, \end{array} \right. \] where DD is a bounded set in Rd\mathbb{R}^{d}, VV is a compact metric space in Rk\mathbb{R}^{k}, and for u∈C2(D)u\in C^{2}(D) and (x,v)∈D×V(x,v)\in D\times V, L(x,v)u(x):=12∑i,j=1d(σσ∗)i,j(x,v)∂2u∂xi∂xj(x)+∑i=1dbi(x,v)∂u∂xi(x).\mathcal{L}(x,v)u(x):=\frac{1}{2}\sum_{i,j=1}^{d}(σσ^{\ast})_{i,j}(x,v)\frac{\partial^{2}u}{\partial x_{i}\partial x_{j}}(x) +\sum_{i=1}^{d}b_{i}(x,v)\frac{\partial u}{\partial x_{i}}(x).

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