Fuzzy Identification Method in Nonlinear System Based on G-K Clustering Algorithm

摘要：

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.

关键词： T-S fuzzy model G-K clustering algorithm Orthogonal least square Fuzzy identification

作者: Shi JianZhong Han Pu Jiao SongMing Wang DongFeng

作者单位: School of Control Science and Engineering, North China Electric Power University, Beijing 102206 School of Control Science and Engineering, North China Electric Power University, Baoding 071003

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 212-215

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）