A T-S fuzzy iterative identification method via objective-satisfactory cluster analysis

Author

Na Wang ; Chaofang Hu ; Wuxi Shi ; Chunbo Xiu ; Yimei Chen

Author_Institution

Sch. of Electr. Eng. & Autom., Tianjin Polytech. Univ., Tianjin, China

fYear

2015

fDate

23-25 May 2015

Firstpage

6495

Lastpage

6499

Abstract

A T-S fuzzy iterative identification method via Objective-Satisfactory Cluster Analysis is proposed in this paper. During the iteration, an Objective-Satisfactory Cluster Analysis algorithm, which combined the Enhanced Objective Cluster Analysis algorithm and the Gustafson-Kessel method is presented. Thus the accuracy and the robustness of the premise of T-S model are guaranteed. Then the consequent parameters are quickly estimated by the Stable Kalman Filter algorithm. The effectiveness of the presented method is proved by the pH-neutralization process.

Keywords

Kalman filters; fuzzy set theory; iterative methods; parameter estimation; pattern clustering; Gustafson-Kessel method; T-S fuzzy iterative identification method; T-S model; consequent parameter estimation; enhanced objective cluster analysis algorithm; objective-satisfactory cluster analysis algorithm; pH-neutralization process; stable Kalman filter algorithm; Accuracy; Algorithm design and analysis; Clustering algorithms; Computational modeling; Indexes; Noise; Partitioning algorithms; Objective Cluster Analysis; T-S model; fuzzy identification; iterative; satisfactory;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2015 27th Chinese

Conference_Location

Qingdao

Print_ISBN

978-1-4799-7016-2

Type

conf

DOI

10.1109/CCDC.2015.7161990

Filename

7161990