Multiscale Linear-Quadratic Stochastic Optimal Control With Multiplicative Noise

TL;DR

This paper analyzes the asymptotic behavior of multiscale stochastic linear-quadratic control problems with multiplicative noise, proposing approximation methods based on differential Riccati equations and singular perturbation theory.

Contribution

It introduces two novel approximation techniques for the value function of multiscale stochastic control problems using singular perturbation and Riccati equations.

Findings

Proposes two approximation methods for the value function.

Utilizes Tikhonov theorem for asymptotic analysis.

Addresses stability issues in coupled Riccati equations.

Abstract

We investigate the asymptotic properties of a finite-time horizon linear-quadratic optimal control problem driven by a multiscale stochastic process with multiplicative Brownian noise. We approach the problem by considering the associated differential Riccati equation and reformulating it as a classical and deterministic singular perturbation problem. Asymptotic properties of this deterministic problem can be gathered from the well-known Tikhonov Theorem. Consequently, we are able to propose two approximation methods to the value function of the stochastic optimal control problem. The first is by constructing an approximately optimal control process whilst the second is by finding the direct limit to the value function. Both approximation methods rely on the existence of a solution to a coupled differential-algebraic Riccati equation with certain stability properties - this is the main difficulty of the paper.