Online identification of evolving Takagi-Sugeno-Kang fuzzy models for crane systems

被引：54

作者：

Precup, Radu-Emil ^{[1
]}

Filip, Horatiu-Ioan ^{[1
]}

Radac, Mircea-Bogdan ^{[1
]}

Petriu, Emil M. ^{[2
]}

Preitl, Stefan ^{[1
]}

Dragos, Claudia-Adina ^{[1
]}

机构：

[1] Politech Univ Timisoara, Dept Automat & Appl Informat, RO-300223 Timisoara, Romania

[2] Univ Ottawa, Sch Elect Engn & Comp Sci, Ottawa, ON K1N 6N5, Canada

来源：

APPLIED SOFT COMPUTING | 2014年 / 24卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

Crane systems; Evolving Takagi-Sugeno-Kang fuzzy models; Online identification algorithms; Pendulum-crane laboratory equipment; Potentials of new data points; Sum of squared errors; INPUT SELECTION; SERVO SYSTEM; DESIGN; OPTIMIZATION; CONTROLLER; ALGORITHM; SEARCH;

D O I：

10.1016/j.asoc.2014.01.013

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper suggests new evolving Takagi-Sugeno-Kang (TSK) fuzzy models dedicated to crane systems. A set of evolving TSK fuzzy models with different numbers of inputs are derived by the novel relatively simple and transparent implementation of an online identification algorithm. An input selection algorithm to guide modeling is proposed on the basis of ranking the inputs according to their important factors after the first step of the online identification algorithm. The online identification algorithm offers rule bases and parameters which continuously evolve by adding new rules with more summarization power and by modifying existing rules and parameters. The potentials of new data points are used with this regard. The algorithm is applied in the framework of the pendulum-crane system laboratory equipment. The evolving TSK fuzzy models are tested against the experimental data and a comparison with other TSK fuzzy models and modeling approaches is carried out. The comparison points out that the proposed evolving TSK fuzzy models are simple and consistent with both training data and testing data and that these models outperform other TSK fuzzy models. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：1155 / 1163

页数：9

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