Statistical bilinearization in stochastic nonlinear dynamics

Author

van de Wouw, N. ; Nijmeijer, H. ; van Campen, D.H.

Author_Institution

Dept. of Mech. Eng., Eindhoven Univ. of Technol., Netherlands

Volume

3

fYear

2000

fDate

2000

Firstpage

394

Abstract

A response approximation method for stochastically excited, nonlinear, dynamic systems is presented. Herein, the output of the nonlinear system is approximated by a finite-order Volterra series. The original, nonlinear system is replaced by a bilinear system in order to determine the kernels of this Volterra series. The parameters of the bilinear system are determined by minimizing the difference between the original system and the bilinear system in a statistical sense. Application to a piece-wise linear system illustrates the effectiveness of this approach in approximating truly nonlinear, stochastic response phenomena in both the statistical moments and the power spectral density of the response of this system in case of a white noise excitation

Keywords

Volterra series; nonlinear dynamical systems; stochastic processes; white noise; Volterra series; bilinear system; finite-order Volterra series; piece-wise linear system; power spectral density; statistical bilinearization; statistical moments; stochastic nonlinear dynamics; stochastically excited nonlinear dynamic systems; white noise excitation; Approximation methods; Kernel; Nonlinear dynamical systems; Nonlinear systems; Piecewise linear approximation; Piecewise linear techniques; Polynomials; Stochastic processes; Stochastic resonance; Vehicle dynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Control of Oscillations and Chaos, 2000. Proceedings. 2000 2nd International Conference

Conference_Location

St. Petersburg

Print_ISBN

0-7803-6434-1

Type

conf

DOI

10.1109/COC.2000.874266

Filename

874266