Modularly structured B-spline networks for internal model control

Author

Menken, G.-J.

Author_Institution

Inst. of Autom. Technol., Bremen Univ.

Volume

3

fYear

1997

fDate

4-6 Jun 1997

Firstpage

2001

Abstract

A method is introduced to weaken the problems arising when a complex nonlinear process has to be controlled. The proposed method is based on the use of modularly structured B-spline networks (MBSN) which are integrated in an internal model control (IMC) structure. It is shown that the networks are suitable for this control strategy due to their simple mathematical description allowing model inversion in an easy way. An example is given to illustrate the advantages over other neural based methods using separate networks considered as controllers which have to be trained additionally to the process modelling network

Keywords

closed loop systems; inverse problems; large-scale systems; model reference adaptive control systems; neurocontrollers; nonlinear control systems; robust control; B-spline networks; associative memory networks; closed loop systems; complex nonlinear process; internal model control; inverse problem; neural networks; neurocontrol; robust control; Associative memory; Automatic control; Automation; Computer aided analysis; Control systems; Design engineering; Mathematical model; Nonlinear control systems; Nonlinear dynamical systems; Spline;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1997. Proceedings of the 1997

Conference_Location

Albuquerque, NM

ISSN

0743-1619

Print_ISBN

0-7803-3832-4

Type

conf

DOI

10.1109/ACC.1997.611039

Filename

611039