Fuzzy system identification and predictive control of load system in power plant

Author

Huaguang, Zhang ; Bien, Zeungnam

Author_Institution

Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea

Volume

1

fYear

1998

fDate

4-9 May 1998

Firstpage

342

Abstract

We use the T-S fuzzy model to express dynamic systems, and present an online identification algorithm for its parameters and structures. A multivariable fuzzy generalized predictive control approach is put forward based on the identified fuzzy model by means of Clark´s principle of single-variable generalized predictive control, some of whose performances are analyzed in detail. A simulation study for the multivariable load control system of an electric generating unit shows that the approach is superior to a conventional load control system

Keywords

fuzzy control; identification; load regulation; multivariable control systems; predictive control; T-S fuzzy model; dynamic systems; fuzzy system identification; load control system; multivariable fuzzy generalized predictive control; online identification algorithm; Control systems; Fuzzy control; Fuzzy systems; Load flow control; Nonlinear dynamical systems; Power generation; Power system modeling; Predictive control; Predictive models; Stability analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7584

Print_ISBN

0-7803-4863-X

Type

conf

DOI

10.1109/FUZZY.1998.687509

Filename

687509