Infinite Horizon and Ergodic Optimal Quadratic Control for an Affine Equation with Stochastic Coefficients

TL;DR

This paper develops a framework for solving infinite horizon and ergodic quadratic stochastic control problems with affine equations and stochastic coefficients, using backward stochastic Riccati equations.

Contribution

It introduces a novel approach involving backward stochastic Riccati and dual equations for optimal control synthesis in complex stochastic systems.

Findings

Existence of solutions to the Riccati equations is established.

Optimal control synthesis is achieved through limit procedures.

Framework applies to systems with stochastic coefficients and affine perturbations.

Abstract

We study quadratic optimal stochastic control problems with control dependent noise state equation perturbed by an affine term and with stochastic coefficients. Both infinite horizon case and ergodic case are treated. To this purpose we introduce a Backward Stochastic Riccati Equation and a dual backward stochastic equation, both considered in the whole time line. Besides some stabilizability conditions we prove existence of a solution for the two previous equations defined as limit of suitable finite horizon approximating problems. This allows to perform the synthesis of the optimal control.