Identification of a class of nonlinear parametrically varying models

Author

Previdi, E. ; Lovera, M.

Author_Institution

Dipt. di Elettron. e Inf., Politec. di Milano, Milan, Italy

fYear

2001

fDate

4-7 Sept. 2001

Firstpage

3086

Lastpage

3091

Abstract

A novel class of linear time-varying models is proposed for nonlinear system identification purposes. These models are linear in the parameters, which are time-varying according to a nonlinear dynamic law. A specific parameter tuning algorithm is presented, which is based only on input/output measurements, but which also provides an estimate of the time-varying behaviour of the parameters. So, a Linear Parameter Varying (LPV) model is obtained to which is possible to apply the robust control techniques for LPV systems. Finally, some interesting relations between this model class and the Local Model Network (LMN) family are discussed in the framework of the LPV systems obtained by convex combination of Linear-Time-Invariant (LTI) systems.

Keywords

linear parameter varying systems; nonlinear control systems; parameter estimation; robust control; time-varying systems; LMN; LPV model; LTI systems; input/output measurements; linear parameter varying model; linear time-varying models; linear-time-invariant systems; local model network; nonlinear dynamic law; nonlinear parametrically varying model identification; nonlinear system identification; parameter tuning algorithm; robust control techniques; time-varying parameter behaviour estimation; time-varying parameters; Computational modeling; Data models; Dynamic scheduling; Neural networks; Performance analysis; Solid modeling; Vectors; Identification methods; Neural Networks; Time Varying Systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (ECC), 2001 European

Conference_Location

Porto

Print_ISBN

978-3-9524173-6-2

Type

conf

Filename

7076405