Stability analysis of T-S fuzzy partially coupled complex networks with pinning impulsive controllers by step function method

被引：0
|
作者：
Yang, Shiju [1 ,2 ]
Huang, Tingting [1 ,2 ]
Ruan, Dongmei [1 ,2 ]
He, Hongsen [1 ,2 ]
机构：
[1] Chongqing Technol & Business Univ, Chongqing Key Lab Intelligent Percept & BlockChain, Chongqing 400067, Peoples R China
[2] Chongqing Technol & Business Univ, Sch Artificial Intelligence, Chongqing 400067, Peoples R China
来源：
FUZZY SETS AND SYSTEMS | 2025年 / 507卷
基金：
中国国家自然科学基金;
关键词：
T-S fuzzy partially coupled complex networks; Stability analysis; Pinning impulsive control; Step-function method; DYNAMICAL NETWORKS; OUTER SYNCHRONIZATION; SYSTEMS;
D O I：
10.1016/j.fss.2025.109318
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper mainly discusses the stability of T-S fuzzy partially coupled complex networks (T-S FPCCNs) with pinning impulsive control. Different from the traditional impulsive control method, the analysis process of the stability can be divided into two parts by adopting the step-function method (the first part is one-span step-function and the second part is multi-span step-function). Then the stability of T-S fuzzy partially coupled complex networks with pinning impulsive control can be analyzed. In addition, the novel pinning impulsive controllers can be designed to ensure the network to achieve globally uniformly attractively stable (GUAS). Furthermore, a comparison system is constructed by using regrouping method and impulsive control theory, and several new sufficient criterions are given to ensure the stability of the T-S FPCCNs. Finally, the correctness of theoretical analysis is proved by experimental cases.
引用
收藏
页数：15
相关论文
共 50 条
  • [41] Asymptotic and robust stability of T-S fuzzy genetic regulatory networks with time-varying delays
    Liu, Jinliang
    Yue, Dong
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2012, 22 (08) : 827 - 840
  • [42] Robust Exponential Stability Criteria for T-S Fuzzy Stochastic Delayed Neural Networks of Neutral Type
    Muralisankar, S.
    Gopalakrishnan, N.
    Balasubramaniam, P.
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2011, 30 (06) : 1617 - 1641
  • [43] Sampled-data exponential synchronization of complex dynamical networks with time-varying delays and T-S fuzzy nodes
    Huang, Xiaojie
    Cao, Xuerui
    Ma, Yuechao
    COMPUTATIONAL & APPLIED MATHEMATICS, 2022, 41 (02):
  • [44] Stability analysis and design of T-S fuzzy control system with simplified linear rule consequent
    Li, N
    Li, SY
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2004, 34 (01): : 788 - 795
  • [45] Stability analysis and state feedback control of continuous-time T-S fuzzy systems via a new switched fuzzy Lyapunov function approach
    Zhai, Ding
    Lu, An-Yang
    Dong, Jiuxiang
    Zhang, Qing-Ling
    APPLIED MATHEMATICS AND COMPUTATION, 2017, 293 : 586 - 599
  • [46] Hybrid L 1 x l 1-gain analysis of T-S fuzzy positive impulsive systems
    Zhang, Kexin
    Chen, Wu-Hua
    Lu, Xiaomei
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2022, 359 (15): : 8218 - 8242
  • [47] Lagrange Stability for T-S Fuzzy Memristive Neural Networks with Time-Varying Delays on Time Scales
    Xiao, Qiang
    Zeng, Zhigang
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (03) : 1091 - 1103
  • [48] Novel Stability Criteria of T-S Fuzzy Hopfield Neural Networks with Time-varying Delays and Uncertainties
    Zhou, C. G.
    Zeng, X. Q.
    Yu, J. J.
    PROCEEDINGS OF THE 2014 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2014, : 2843 - 2850
  • [49] Stability analysis of sampled-data fuzzy controller for nonlinear systems based on switching T-S fuzzy model
    Lam, H. K.
    NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2009, 3 (04) : 418 - 432
  • [50] Set-membership estimation for T-S fuzzy complex networks: a dynamic coding-decoding mechanism
    Hu, Changzhen
    Ding, Sanbo
    Rong, Nannan
    NONLINEAR DYNAMICS, 2025, : 17041 - 17056
12345