A Hybrid Clustering Algorithm for Fuzzy Functions System Identification

SHI Jianzhong; HAN Pu; WANG Dongfeng; JIAO Songming

Volume 40 Issue 3

Jun. 2011

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INFORMATION AND CONTROL > 2011 > 40(3): 387-392,400.

SHI Jianzhong, HAN Pu, WANG Dongfeng, JIAO Songming. A Hybrid Clustering Algorithm for Fuzzy Functions System Identification[J]. INFORMATION AND CONTROL, 2011, 40(3): 387-392,400.

Citation:

SHI Jianzhong, HAN Pu, WANG Dongfeng, JIAO Songming. A Hybrid Clustering Algorithm for Fuzzy Functions System Identification[J]. INFORMATION AND CONTROL, 2011, 40(3): 387-392,400.

Citation:

SHI Jianzhong, HAN Pu, WANG Dongfeng, JIAO Songming. A Hybrid Clustering Algorithm for Fuzzy Functions System Identification[J]. INFORMATION AND CONTROL, 2011, 40(3): 387-392,400.

A Hybrid Clustering Algorithm for Fuzzy Functions System Identification

School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China

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Received Date: August 02, 2010
Revised Date: March 03, 2011
Published Date: June 19, 2011

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Abstract

Abstract

A fuzzy function system identification algorithm based on hybrid clustering method is proposed on account of the problems of uncertain structure and parameter identification complexity of conventional fuzzy system.Compared with general fuzzy function systems,the new algorithm combines with the sample distance of fuzzy C-means and fuzzy C-regression model.In model prediction section,the membership degree of each input variable is computed by Gaussian function,and the input vector's membership degree is obtained by the fuzziness operator of input variable's membership degree.The algorithm is applied separately to Box-Jenkins gas furnace data,a double entry single output nonlinear system and Mackey-Glass chaotic time series.Experimental results show that this algorithm has good identification effect,which validates the effectiveness and practicability of the algorithm.
- fuzzy function,
- fuzzy C-means,
- fuzzy C-regression model,
- fuzzy identification,
- least square

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References (23)

References

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