Mechatronic and computational intelligence

Author

Schröder, Dierk

Author_Institution

Tech. Univ. of Munich, Munich

fYear

2007

fDate

26-28 Sept. 2007

Firstpage

1

Lastpage

6

Abstract

In this paper we present identification methods for nonlinear mechatronic systems. First, we consider a system consisting of a known linear part and an unknown static nonlinearity. With this approach, using an intelligent observer, it is possible to identify the nonlinear characteristic and to estimate all unmeasurable system states. The identification result of the nonlinearity and the estimated system states are used to improve the controller performance. Secondly, the first approach is extended to systems where both, the linear parameters and the nonlinear characteristic are unknown. This is achieved by implementing the intelligent observer as a structured recurrent neural network.

Keywords

identification; mechatronics; nonlinear systems; state estimation; computational intelligence; identification methods; intelligent observer; nonlinear mechatronic systems; structured recurrent neural network; unmeasurable system states; Competitive intelligence; Computational intelligence; Control systems; Intelligent networks; Intelligent structures; Mechatronics; Nonlinear control systems; Observers; Recurrent neural networks; State estimation; intelligent observer; nonlinear system; recurrent neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

AFRICON 2007

Conference_Location

Windhoek

Print_ISBN

978-1-4244-0987-7

Electronic_ISBN

978-1-4244-0987-7

Type

conf

DOI

10.1109/AFRCON.2007.4401513

Filename

4401513