Model reference adaptive control of nonlinear systems using RLLM networks

Author

Ali, A. ; Ashfaq, M. ; Schmid, Chr.

Author_Institution

Dept. of Electr. Eng., Ruhr-Univ., Bochum, Germany

Volume

3

fYear

2000

fDate

2000

Firstpage

1659

Abstract

A model reference adaptive controller for nonlinear systems is implemented using rectangular local linear model (RLLM) network approach. An RLLM network is used to identify the plant as NARX model. Another network of the same kind consisting of linear controllers is tuned to achieve the closed-loop behaviour of a linear reference model. A master slave configuration is realised to decide the activation of candidate linear controllers in the controller network. The implemented control scheme is tested in simulations and real-time control on a hydraulic positioning system

Keywords

MIMO systems; adaptive control; autoregressive processes; closed loop systems; hydraulic control equipment; identification; learning (artificial intelligence); model reference adaptive control systems; neural nets; nonlinear systems; MIMO systems; NARX model; adaptive control; closed-loop systems; hydraulic positioning system; identification; learning algorithm; master slave configuration; model reference adaptive control; neural networls; nonlinear systems; real-time systems; rectangular local linear model network; Adaptive control; Artificial neural networks; Control engineering; Control system synthesis; Linear approximation; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2000. Proceedings of the 2000

Conference_Location

Chicago, IL

ISSN

0743-1619

Print_ISBN

0-7803-5519-9

Type

conf

DOI

10.1109/ACC.2000.879483

Filename

879483