The linear quadratic regulator problem for a class of controlled systems modeled by singularly perturbed Itô differential equations. (English) Zbl 1242.93078

Dragan, Vasile; Mukaidani, Hiroaki; Shi, Peng

SIAM J. Control Optim. 50, No. 1, 448-470 (2012).

Summary: This paper discusses an infinite-horizon Linear Quadratic (LQ) optimal control problem involving state- and control-dependent noise in singularly perturbed stochastic systems. First, an asymptotic structure along with a stabilizing solution for the stochastic Algebraic Riccati Equation (ARE) are newly established. It is shown that the dominant part of this solution can be obtained by solving a parameter-independent system of coupled Riccati-type equations. Moreover, sufficient conditions for the existence of the stabilizing solution to the problem are given. A new sequential numerical algorithm for solving the reduced-order AREs is also described. Based on the asymptotic behavior of the ARE, a class of \(O(\sqrt{\varepsilon})\) approximate controller that stabilizes the system is obtained. Unlike the existing results in singularly perturbed deterministic systems, it is noteworthy that the resulting controller achieves an \(O(\varepsilon)\) approximation to the optimal cost of the original LQ optimal control problem. As a result, the proposed control methodology can be applied to practical applications even if the value of the small parameter \(\varepsilon\) is not precisely known.

MSC:

93C70	Time-scale analysis and singular perturbations in control/observation systems
93E20	Optimal stochastic control
93B40	Computational methods in systems theory (MSC2010)
49N10	Linear-quadratic optimal control problems

Keywords:

singularly perturbed control systems; asymptotic behavior; stabilizing solution