Stability analysis of recurrent type-2 TSK fuzzy systems with nonlinear consequent part

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• 作者：Jafar Tavoosi ; Amir Abolfazl Suratgar…
• 关键词：Recurrent type ; 2 fuzzy ; Stability analysis ; Nonlinear consequent
• 刊名：Neural Computing and Applications
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：28
• 期：1
• 页码：47-56
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Probability and Statistics in Computer Science; Computational Science and Engineering; Image Processing and Computer Visi
• 出版者：Springer London
• ISSN：1433-3058
• 卷排序：28

文摘

A necessary condition for stability of a class of recurrent type-2 TSK fuzzy systems is presented. In this system, the antecedent part is indeed represented by interval Gaussian type-2 fuzzy set, and the consequent part is an ordinary nonlinear function of the system’s inputs. In the proposed method, at first a type-2 fuzzy model is established, and then an LMI-based stability analysis of the model is fully discussed. Two first-order systems (one stable and one unstable) and two second-order systems (one stable and one unstable) are then considered as proper case studies. The simulation results easily approve the effectiveness of the proposed method.