Exponential Stability of Fractional-Order Impulsive Control Systems With Applications in Synchronization

被引:119
作者
Yang, Shuai [1 ]
Hu, Cheng [1 ]
Yu, Juan [1 ]
Jiang, Haijun [1 ]
机构
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China
基金
中国国家自然科学基金;
关键词
Synchronization; Neural networks; Control systems; Biological system modeling; Asymptotic stability; Stability criteria; Cohen-Grossberg neural network; exponential stability; exponential synchronization; generalized Caputo fractional derivative; impulsive control; MITTAG-LEFFLER STABILITY; GROSSBERG NEURAL-NETWORKS; PROJECTIVE SYNCHRONIZATION; ACTIVATION FUNCTIONS; GLOBAL STABILITY; STABILIZATION; EXISTENCE;
D O I
10.1109/TCYB.2019.2906497
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates exponential stability of fractional-order impulsive control systems (FICSs) and exponential synchronization of fractional-order Cohen-Grossberg neural networks (FCGNNs). First, under the framework of the generalized Caputo fractional-order derivative, some new results for fractional-order calculus are established by mainly using L'Hospital's rule and Laplace transform. Besides, FICSs are translated into impulsive differential equations with fractional-order via utilizing the definition of Dirac function, which reveals that the effect of impulsive control on fractional systems is dependent of the order of the addressed systems. Furthermore, exponential stability of FICSs is proposed and some novel criteria are obtained by applying average impulsive interval and the method of induction. As an application of the stability for FICSs, exponential synchronization of FCGNNs is considered and several synchronization conditions are established under impulsive control. Finally, several numerical examples are provided to illustrate the effectiveness of the derived results.
引用
收藏
页码:3157 / 3168
页数:12
相关论文
共 50 条
  • [41] Designing a switching law for Mittag-Leffler stability in nonlinear singular fractional-order systems and its applications in synchronization
    Hong, Duong Thi
    Thuan, Do Duc
    Thanh, Nguyen Truong
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2025, 140
  • [42] Exponential Stability of Impulsive Fractional Switched Systems With Time Delays
    He, Danhua
    Xu, Liguang
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2021, 68 (06) : 1972 - 1976
  • [43] Exponential ultimate boundedness of fractional-order differential systems via periodically intermittent control
    Xu, Liguang
    Liu, Wen
    Hu, Hongxiao
    Zhou, Weisong
    NONLINEAR DYNAMICS, 2019, 96 (02) : 1665 - 1675
  • [44] Asymptotic stability of delayed fractional-order neural networks with impulsive effects
    Wang, Fei
    Yang, Yongqing
    Hu, Manfeng
    NEUROCOMPUTING, 2015, 154 : 239 - 244
  • [45] Prediction-based feedback control and synchronization algorithm of fractional-order chaotic systems
    Soukkou, Ammar
    Boukabou, Abdelkrim
    Leulmi, Salah
    NONLINEAR DYNAMICS, 2016, 85 (04) : 2183 - 2206
  • [46] Exponential stabilization of fractional-order continuous-time dynamic systems via event-triggered impulsive control
    Yu, Nanxiang
    Zhu, Wei
    NONLINEAR ANALYSIS-MODELLING AND CONTROL, 2022, 27 (03): : 592 - 608
  • [47] Asymptotic and finite-time synchronization of fractional-order multiplex networks with time delays by adaptive and impulsive control
    Luo, Tianjiao
    Wang, Qi
    Jia, Qilong
    Xu, Yao
    NEUROCOMPUTING, 2022, 493 : 445 - 461
  • [48] Event-triggered impulsive chaotic synchronization of fractional-order differential systems
    Yu, Nanxiang
    Zhu, Wei
    APPLIED MATHEMATICS AND COMPUTATION, 2021, 388
  • [49] Impulsive anti-synchronization control for fractional-order chaotic circuit with memristor
    Fanqi Meng
    Xiaoqin Zeng
    Zuolei Wang
    Indian Journal of Physics, 2019, 93 : 1187 - 1194
  • [50] Mittag-Leffler stability, control, and synchronization for chaotic generalized fractional-order systems
    Abed-Elhameed, Tarek M.
    Aboelenen, Tarek
    ADVANCES IN CONTINUOUS AND DISCRETE MODELS, 2022, 2022 (01):