Nonlinear stochastic control via stationary probability density functions

Author

Crespo, L.G. ; Sun, J.Q.

Author_Institution

Dept. of Mech. Eng., Delaware Univ., Newark, DE, USA

Volume

3

fYear

2002

fDate

2002

Firstpage

2029

Abstract

Presents a control strategy for externally excited stochastic systems with parametric uncertainties. The objective is to drive the system to match a target probability density function (PDF) in steady state. The control consists of a nonlinear feedback and a switching term for handling parameter uncertainty. The fast rate of convergence to the stationary PDF is observed in the time evolution of the mean and variance of the closed loop system through Monte Carlo simulations. The dependence of the control performance on the number of terms in the polynomial control series and on the rate of convergence to the steady state distribution are studied numerically. This control design based on the stationary PDF is also applied to the tracking of a time-varying probability density function.

Keywords

closed loop systems; control system synthesis; convergence; nonlinear control systems; probability; sampled data systems; stochastic processes; stochastic systems; uncertain systems; Monte Carlo simulations; control strategy; nonlinear feedback; nonlinear stochastic control; parametric uncertainties; polynomial control series; random vibrations; rate of convergence; robust control; stationary probability density functions; switching term; Closed loop systems; Control systems; Convergence; Feedback; Probability density function; Steady-state; Stochastic processes; Stochastic systems; Uncertain systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2002. Proceedings of the 2002

ISSN

0743-1619

Print_ISBN

0-7803-7298-0

Type

conf

DOI

10.1109/ACC.2002.1023933

Filename

1023933