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一种基于模糊规则的非线性系统快速模糊辨识方法
引用本文:刘福才,关新平,裴润.一种基于模糊规则的非线性系统快速模糊辨识方法[J].系统仿真学报,2002,14(5):547-550.
作者姓名:刘福才  关新平  裴润
作者单位:1. 哈尔滨工业大学航天学院控制工程系,哈尔滨,150001燕山大学电气工程学院自动化系,秦皇岛,066004
2. 燕山大学电气工程学院自动化系,秦皇岛,066004
3. 哈尔滨工业大学航天学院控制工程系,哈尔滨,150001
基金项目:国家杰出青年基金(69925308),黑龙江省自然科学基金资助
摘    要:针对以往模糊建模方法中算法中算法过于复杂的问题,提出了一种简单而有交的复杂系统模糊建模新方法。该方法是基于输入空间的模糊划分,计算给定样本在各模糊子空间的隶属度,并列用卡尔曼滤波算法辨识模糊模型的结论参数。整个辨识过程与模糊聚类方法和误差反馈学习方法相比所需的CPU时间最短。最后通过著名的Box-Jenkins煤气炉数据仿真结果证明了该方法的有效性与实用性。

关 键 词:模糊规则  非线性系统  快速模糊辨识方法  模糊if-then规则  卡尔曼滤波算法
文章编号:1004-731X(2002)05-0547-04
修稿时间:2001年5月8日

A Fast Fuzzy Identification Method in Nonlinear System Based on Fuzzy Logic Rules
LIU Fu-cai,GUAN Xin-ping,PEI Run.A Fast Fuzzy Identification Method in Nonlinear System Based on Fuzzy Logic Rules[J].Journal of System Simulation,2002,14(5):547-550.
Authors:LIU Fu-cai    GUAN Xin-ping  PEI Run
Institution:LIU Fu-cai1,2,GUAN Xin-ping2,PEI Run1
Abstract:In accordance with the problems that the algorithm is too complex in the past fuzzy modeling methods, this article proposes a new method of fuzzy modeling for complex system. The method is simple and powerful. This method is based on fuzzy partition of input space, and it calculates the grade of membership of given patterns in each fuzzy subspace with the consequence parameters identification obtained by using Kalman filtering algorithm. The whole identification process takes much less CPU time than the fuzzy clustering method and the error-feedback learning algorithm. Finally the effectiveness and practicability of this method is demonstrated by the simulation results of the famous Box-Jenkins gas furnace data.
Keywords:fuzzy identification  fuzzy partition  fuzzy if-then rules  Kalman filtering algorithm
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