Finite-time stability and synchronization of memristor-based fractional-order fuzzy cellular neural networks

被引：123
|
作者：
Zheng, Mingwen [1 ,2 ]
Li, Lixiang [3 ]
Peng, Haipeng [3 ]
Xiao, Jinghua [1 ,4 ]
Yang, Yixian [3 ]
Zhang, Yanping [2 ]
Zhao, Hui [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China
[2] Shandong Univ Technol, Sch Sci, Zibo 255000, Peoples R China
[3] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Informat Secur Ctr, Beijing 100876, Peoples R China
[4] Beijing Univ Posts & Telecommun, State Key Lab Informat Photon & Opt Commun, Beijing 100876, Peoples R China
来源：
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2018年 / 59卷
基金：
中国国家自然科学基金;
关键词：
Finite-time stability; MFFCNN; Gronwall-Bellman inequality; Linear feedback controller; EXPONENTIAL LAG SYNCHRONIZATION; TURBINE GOVERNING SYSTEM; MITTAG-LEFFLER STABILITY; PROJECTIVE SYNCHRONIZATION; ASSOCIATIVE MEMORY; NONLINEAR DYNAMICS; EXISTENCE;
D O I：
10.1016/j.cnsns.2017.11.025
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper mainly studies the finite-time stability and synchronization problems of memristor-based fractional-order fuzzy cellular neural network (MFFCNN). Firstly, we discuss the existence and uniqueness of the Filippov solution of the MFFCNN according to the Banach fixed point theorem and give a sufficient condition for the existence and uniqueness of the solution. Secondly, a sufficient condition to ensure the finite-time stability of the MFFCNN is obtained based on the definition of finite-time stability of the MFFCNN and Gronwall-Bellman inequality. Thirdly, by designing a simple linear feedback controller, the finite-time synchronization criterion for drive-response MFFCNN systems is derived according to the definition of finite-time synchronization. These sufficient conditions are easy to verify. Finally, two examples are given to show the effectiveness of the proposed results. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码：272 / 291
页数：20
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