Dynamic modelling and control for a class of non-linear systems using neural nets

Author

Abdulaziz, A. ; Farsi, M.

Author_Institution

Dept. of Electr. & Electron. Eng., Newcastle Upon Tyne, Univ., UK

fYear

1993

fDate

6/15/1905 12:00:00 AM

Firstpage

543

Lastpage

548

Abstract

The paper describes a new neural network Controller using an IMC structure (NIMC). The structure is suitable for control of discrete-time SISO systems containing nonlinearities. Two design steps are assumed: (1) the controller is designed for optimal set-point tracking and disturbance rejection or model uncertainty and (2) the controller is detuned for robust performance. Comparative studies between NIMC and a conventional nonlinear adaptive controller is made.

Keywords

control nonlinearities; control system synthesis; discrete time systems; identification; neural nets; nonlinear control systems; design; discrete-time SISO systems; disturbance rejection; dynamic modelling; internal model control; model uncertainty; neural nets; nonlinear control systems; optimal set-point tracking; robust performance; synthesis; Linear approximation; Linear systems; Neural networks; Neurons; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear equations; Performance analysis; System identification; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, 1993. Conference Proceedings, ISIE'93 - Budapest., IEEE International Symposium on

Conference_Location

Budapest, Hungary

Print_ISBN

0-7803-1227-9

Type

conf

DOI

10.1109/ISIE.1993.268747

Filename

268747