Stabilization in probability of nonlinear stochastic systems with guaranteed cost

Author

Battilotti, S. ; De Santis, A.

Author_Institution

Dipartimento di Inf. e Sistemistica, Rome Univ., Italy

Volume

3

fYear

2000

fDate

2000

Firstpage

2456

Abstract

We deal with nonlinear dynamical systems, consisting of a linear nominal part perturbed by model uncertainties, nonlinearities and both additive and multiplicative random noise, modeled as a Wiener process. In particular, we study the problem of finding suitable measurement feedback control laws such that the resulting closed-loop system is stable in some probabilistic sense and a given cost functional is minimized. We give a Lyapunov-based separation result which splits the control design into a state feedback problem and a filtering problem

Keywords

Lyapunov methods; closed loop systems; feedback; filtering theory; minimisation; nonlinear control systems; nonlinear dynamical systems; optimal control; probability; random noise; stability; stochastic systems; uncertain systems; Lyapunov-based separation result; Wiener process; additive random noise; closed-loop system; cost functional minimization; filtering problem; guaranteed cost; linear nominal part; measurement feedback control laws; model uncertainties; multiplicative random noise; nonlinear dynamical systems; nonlinear stochastic system probability; stabilization; state feedback problem; Additive noise; Asymptotic stability; Control systems; Cost function; Observers; Optimal control; Output feedback; State feedback; State-space methods; Stochastic systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2000. Proceedings of the 39th IEEE Conference on

Conference_Location

Sydney, NSW

ISSN

0191-2216

Print_ISBN

0-7803-6638-7

Type

conf

DOI

10.1109/CDC.2000.914170

Filename

914170