On-line fuzzy identification for advanced intelligent controller

Author

Blazic, Sago ; Skrjanc, Igor ; Gerksic, Samo ; Dolanc, Gregor ; Strmcnik, Stanko ; Hadjiski, Mincho B. ; Stathaki, Anna

Author_Institution

Fac. of Electr. Eng., Ljubljana Univ., Slovenia

Volume

2

fYear

2003

fDate

10-12 Dec. 2003

Firstpage

912

Abstract

The paper presents the identification issues of the self-tuning nonlinear controller ASPECT* (advanced control algorithms for programmable logic controllers). The controller is implemented on a simple PLC platform with an extra mathematical coprocessor but is intended for the advanced control of complex processes. The model of the controlled plant is obtained by means of experimental modelling using an online learning procedure that combines model identification with pre-and post-identification steps that provide reliable operation. It is shown that acceptable performance of the system is obtained despite the difficult conditions it may encounter, such as nonlinearity of the plant, slowly varying parameters of the plant, high level noise etc.

Keywords

adaptive control; control nonlinearities; coprocessors; fuzzy control; identification; intelligent control; learning systems; nonlinear control systems; programmable controllers; PLC platform; advanced control algorithms; fuzzy identification; intelligent controller; learning system; mathematical coprocessor; model identification; plant nonlinearity; programmable logic controllers; reliable operation; self tuning nonlinear controller; Adaptive control; Automatic control; Coprocessors; Fuzzy control; Fuzzy neural networks; Helium; Noise level; Process control; Programmable control; Robust control;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Technology, 2003 IEEE International Conference on

Print_ISBN

0-7803-7852-0

Type

conf

DOI

10.1109/ICIT.2003.1290781

Filename

1290781