Reconstructing nonlinear systems

Author

Mees, Alistair I.

Author_Institution

Centre for Applied Dynamics & Optimization, Western Australia Univ., Nedlands, WA, Australia

Volume

3

fYear

1996

fDate

12-15 May 1996

Firstpage

1

Abstract

Identification and modelling of nonlinear systems is not easy. It is known that, in a certain sense, some modelling methods are stronger than others. We describe a systematic and noise-robust approach to building strong models using “pseudo-linear” approximations. Examples of successful applications include a full bifurcation analysis and both quantitative and qualitative description of the dynamics of a non-stationary vibrating string which has both chaotic and non-chaotic regimes

Keywords

bifurcation; chaos; identification; modelling; nonlinear dynamical systems; nonlinear systems; bifurcation analysis; chaotic regimes; embedding theorem; noise-robust approach; nonchaotic regimes; nonlinear system identification; nonlinear system modelling; nonlinear system reconstruction; nonstationary vibrating string dynamics; pseudo-linear approximations; radial basis modelling; strong models; Bifurcation; Chaos; Differential equations; Linear systems; Nonlinear dynamical systems; Nonlinear systems; Pareto analysis; Power system modeling; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on

Conference_Location

Atlanta, GA

Print_ISBN

0-7803-3073-0

Type

conf

DOI

10.1109/ISCAS.1996.541465

Filename

541465