Title :
Cluster optimization for Takagi & Sugeno fuzzy models and its application to a combined cycle power plant boiler
Author :
Sáez, Doris ; Zuniga, R.
Author_Institution :
Dept. of Electr. Eng., Chile Univ., Santiago, Chile
fDate :
June 30 2004-July 2 2004
Abstract :
A new method for cluster number optimization of Takagi & Sugeno models is proposed. A general identification methodology is also described, including a sensitivity analysis for input variable selection. The new method is exemplified using a benchmark problem, i.e., Chen series. After that, the fuzzy models of a combined cycle power plant boiler, using the proposed methodology, are derived.
Keywords :
boilers; fuzzy set theory; fuzzy systems; identification; nonlinear control systems; optimisation; pattern clustering; sensitivity analysis; thermal power stations; Chen series; Takagi-Sugeno fuzzy models; benchmark problem; cluster optimization; cycle power plant boiler; identification; input variable selection; nonlinear control systems; sensitivity analysis;
Conference_Titel :
American Control Conference, 2004. Proceedings of the 2004
Conference_Location :
Boston, MA, USA
Print_ISBN :
0-7803-8335-4
