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一种基于卡尔曼滤波的非线性模型在线模糊辨识算法
引用本文:张学庆,赵乐生,张燕,张超,李华,姜杰. 一种基于卡尔曼滤波的非线性模型在线模糊辨识算法[J]. 制造业自动化, 2007, 29(12): 80-83
作者姓名:张学庆  赵乐生  张燕  张超  李华  姜杰
作者单位:山东莱芜钢铁集团自动化部,山东省莱芜市,271104
摘    要:文章提出一种用于非线性模型在线辨识的模糊算法。该算法将非线性输入输出系统用时变线性系统模型来拟和,并把此非线性系统模型表示成模糊模型的形式,用在线调节模糊模型的方法来辨识时变线性模型的相关参数。本文将递推模糊聚类方法与卡尔曼滤波法用于在线调整模糊模型参数。仿真算例表明了此算法的有效性。

关 键 词:非线性系统 在线辨识 模糊集合 卡尔曼滤波
文章编号:1009-0134(2007)12-0080-04
收稿时间:2007-09-17
修稿时间:2007-09-17

An online fuzzy identification method for nonlinear model based on kalman filter
ZHANG Xue-qing,ZHAO Le-sheng,ZHANG Yan,ZHANG Chao,LI Hua,JIANG Jie. An online fuzzy identification method for nonlinear model based on kalman filter[J]. Manufacturing Automation, 2007, 29(12): 80-83
Authors:ZHANG Xue-qing  ZHAO Le-sheng  ZHANG Yan  ZHANG Chao  LI Hua  JIANG Jie
Abstract:An online fuzzy identification method for nonlinear model is presented. In the method, nonlinear system is substituted by time-varying linear system, and the multi-input and single output model is expressed by fuzzy model. The parameters of the time-varying nonlinear system are identified by method of online adjusting fuzzy mode. In the paper, an online identification algorithm based on recursive fuzzy clustering method is presented. The result of emulation example demonstrated that the method is effective.
Keywords:nonlinear system   online identification   recursive fuzzy clustering   kalman filter
本文献已被 CNKI 维普 万方数据 等数据库收录!
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