Asynchronous finite-time extended dissipative sliding mode control for semi-Markovian jump master-slave neural networks

被引：2
|
作者：
Cheng, Guifang [1 ]
Liu, Hao [1 ]
机构：
[1] Zhengzhou Univ, Sch Math & Stat, Zhengzhou 450001, Peoples R China
来源：
CHAOS SOLITONS & FRACTALS | 2024年 / 179卷
基金：
中国国家自然科学基金;
关键词：
Asynchronous controller; MSNNs; Sliding mode control; Finite-time contractive bound; Extended dissipative; OUTPUT-FEEDBACK CONTROL; EVENT-TRIGGERED CONTROL; SYNCHRONIZATION; SYSTEMS; STABILITY;
D O I：
10.1016/j.chaos.2024.114457
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This paper aims to investigate the finite -time extended dissipative asynchronous sliding mode control (SMC) on semi-Markovian jump master-slave neural networks (MSNNs) subject to event -triggering scheme (ETS) and packet dropout. Considering ETS, packet dropout and network -induced delays, the asynchronous finitetime SMC which is more realistic is designed. Sufficient conditions are obtained that closed -loop system is extended dissipative stochastic finite -time bound. Meantime, we present novel results for closed -loop system on extended dissipative stochastic finite -time contractive bound. Finally, the biological neural network is presented to illustrate the validness of methods.
引用
收藏
页数：11
相关论文
共 50 条
  • [1] Terminal sliding mode control of master-slave system with Markovian jump parameters
    Liu, Xinghua
    Ma, Guoqi
    Xi, Hongsheng
    Wang, Weidong
    2015 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), 2015, : 1078 - 1083
  • [2] Finite-time asynchronous sliding mode control for Markovian jump systems
    Li, Fanbiao
    Du, Chenglong
    Yang, Chunhua
    Wu, Ligang
    Gui, Weihua
    AUTOMATICA, 2019, 109
  • [3] H∞ stochastic synchronization for master-slave semi-Markovian switching system via sliding mode control
    Liu, Xinghua
    Ma, Guoqi
    Jiang, Xiaofeng
    Xi, Hongsheng
    COMPLEXITY, 2016, 21 (06) : 430 - 441
  • [4] Asynchronous finite-time state estimation for semi-Markovian jump neural networks with randomly occurred sensor nonlinearities
    Wang, Yao
    Xu, Shengyuan
    Li, Yongmin
    Chu, Yuming
    Zhang, Zhengqiang
    NEUROCOMPUTING, 2021, 432 : 240 - 249
  • [5] Master-slave synchronization for uncertain Markov jump neural networks with time-delay based on the sliding mode control
    You, Wenjie
    Wang, Tianbo
    AIMS MATHEMATICS, 2024, 9 (01): : 257 - 269
  • [6] Mode-dependent delays for dissipative filtering of stochastic semi-Markovian jump for neural networks
    Aslam, Muhammad Shamrooz
    Li, Qianmu
    Jun Hou
    Hua Qiulong
    ADVANCES IN CONTINUOUS AND DISCRETE MODELS, 2022, 2022 (01):
  • [7] Asynchronous adaptive quantized feedback sliding mode control for semi-markovian jump systems: An event-triggered
    Li, Min
    Liu, Ming
    Zhang, Yingchun
    NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2020, 36
  • [8] Finite-time dissipative synchronization of discrete-time semi-Markovian jump complex dynamical networks with actuator faults
    Sakthivel, N.
    Pallavi, S.
    Ma, Yong-Ki
    Vijayakumar, V.
    SOFT COMPUTING, 2022, 26 (17) : 8371 - 8386
  • [9] Finite-time dissipative control for semi-Markovian jump systems with time-varying delays and generally uncertain transition rates
    Wan, Zijing
    Zhu, Quanxin
    ASIAN JOURNAL OF CONTROL, 2023, 25 (06) : 4370 - 4379
  • [10] Sliding mode control for semi-Markovian jump systems via output feedback
    Wei, Yanling
    Park, Ju H.
    Qiu, Jianbin
    Wu, Ligang
    Jung, Ho Youl
    AUTOMATICA, 2017, 81 : 133 - 141
12345