Title :
Fuzzy identification method in nonlinear system based on G-K clustering algorithm
Author :
JianZhong, Shi ; Pu, Han ; SongMing, Jiao ; Dongfeng, Wang
Author_Institution :
Sch. of Control Sci. & Eng., North China Electr. Power Univ., Beijing, China
Abstract :
In accordance with the problems that the algorithm is too complex in the past fuzzy modeling methods, this article propose a new method of fuzzy modeling for nonlinear system. The method is simple and powerful. In this method, the premise configuration and parameter of this fuzzy model is decided by G-K fuzzy clustering algorithm, and succedent parameter of fuzzy model is identified by orthogonal least square. Finally the effectiveness and practicability of this method is demonstrated by the simulation result of the Box-Jenkins gas furnace data.
Keywords :
fuzzy control; least squares approximations; Box-Jenkins gas furnace data; G-K clustering algorithm; fuzzy identification method; fuzzy modeling method; nonlinear system; orthogonal least square; Clustering algorithms; Furnaces; Fuzzy control; Fuzzy systems; Heuristic algorithms; Least squares methods; Nonlinear control systems; Nonlinear systems; Power engineering and energy; Power system modeling; Fuzzy identification; G-K clustering algorithm; Orthogonal least square; T-S fuzzy model;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5195115
