Stabilization Control for ItO Stochastic System with Indefinite State and Control Weight Costs

TL;DR

This paper develops stabilization conditions for Ito stochastic systems with indefinite weights in the cost functional, extending classical LQ control by deriving a generalized algebraic Riccati equation and linking indefinite and definite cases.

Contribution

It introduces a generalized algebraic Riccati equation approach for stabilization of indefinite stochastic control systems, providing necessary and sufficient conditions.

Findings

Derived a generalized algebraic Riccati equation (GARE) for indefinite stochastic control.

Established equivalence between indefinite and definite stabilization problems.

Provided a Lyapunov-based stabilization criterion using the GARE and SARE.

Abstract

In standard linear quadratic (LQ) control, the first step in investigating infinite-horizon optimal control is to derive the stabilization condition with the optimal LQ controller. This paper focuses on the stabilization of an Ito stochastic system with indefinite control and state weighting matrices in the cost functional. A generalized algebraic Riccati equation (GARE) is obtained via the convergence of the generalized differential Riccati equation (GDRE) in the finite-horizon case. More importantly, the necessary and sufficient stabilization conditions for indefinite stochastic control are obtained. One of the key techniques is that the solution of the GARE is decomposed into a positive semi-definite matrix that satisfies the singular algebraic Riccati equation (SARE) and a constant matrix that is an element of the set satisfying certain linear matrix inequality conditions. Using the equivalence between the GARE and SARE, we reduce the stabilization of the general indefinite case to that of the definite case, in which the stabilization is studied using a Lyapunov functional defined by the optimal cost functional subject to the SARE.