Finite-time non-fragile filtering for nonlinear networked control systems via a mixed time/event-triggered transmission mechanism

被引:5
|
作者
Lu, Zhongda [1 ]
Lu, Junxiao [2 ]
Zhang, Jiaqi [2 ]
Xu, Fengxia [1 ]
机构
[1] Qiqihar Univ, Coll Mech & Elect Engn, Qiqihar 161006, Heilongjiang, Peoples R China
[2] Qiqihar Univ, Coll Comp & Control Engn, Qiqihar 161006, Heilongjiang, Peoples R China
关键词
Interval type-2 Takagi-Sugeno fuzzy model; networked control systems; mixed time; event-triggered transmission mechanism; finite-time non-fragile filter; S FUZZY-SYSTEMS; LINEAR-SYSTEMS; VARYING DELAY; MODEL;
D O I
10.1007/s11768-020-0011-8
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 is aimed at investigating the problem of mixed time/event-triggered finite-time non-fragile filtering for nonlinear networked control systems with delay. First, a fuzzy nonlinear networked control system model is established by interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model, the designed non-fragile filter resolves the filter parameter uncertainties and uses different membership functions from the IT2 T-S fuzzy model. Second, a novel mixed time/event-triggered transmission mechanism is proposed, which decreases the waste of network resources. Next, Bernoulli random variables are used to describe the cases of random switching mixed time/event-triggered transmission mechanism. Then, the error filtering system is designed by considering a Lyapunov function and a sufficient condition of finite-time boundedness. In addition, the existence conditions for the finite-time non-fragile filter are given by the linear matrix inequalities (LMIs). Finally, two simulation results are presented to prove the effectiveness of the obtained method.
引用
收藏
页码:168 / 181
页数:14
相关论文
共 50 条
  • [31] Event-Triggered Finite-Time Tracking Control for Nonlinear Systems via Immersion and Invariance Techniques
    He, Jianchao
    Cheng, Zijun
    Chang, Tianshui
    Liu, Qidong
    Yang, Yang
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 : 1606 - 1619
  • [32] Event-Triggered Finite-Time Tracking Control for Nonlinear Systems via Immersion and Invariance Techniques
    He, Jianchao
    Cheng, Zijun
    Chang, Tianshui
    Liu, Qidong
    Yang, Yang
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 : 1606 - 1619
  • [33] Event-Triggered Global Finite-Time Control for a Class of Uncertain Nonlinear Systems
    Zhang, Cui-Hua
    Yang, Guang-Hong
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2020, 65 (03) : 1340 - 1347
  • [34] Asynchronous Event-Triggered Finite-Time Filtering for Networked Switched T-S Fuzzy Systems
    Gao, Hui
    Shi, Kaibo
    Zhang, Hongbin
    Lv, Hongbo
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2021, 40 (09) : 4279 - 4300
  • [35] Non-fragile observer-based security control for networked systems via event-triggered WTOD protocol
    Liu, Jian
    Wang, Shuailong
    Hu, Bing
    Liu, Jinliang
    Xie, Xiangpeng
    Tian, Engang
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2024, 34 (09) : 5852 - 5872
  • [36] Finite-time non-fragile boundary feedback control for a class of nonlinear parabolic systems
    Wei, Chengzhou
    Li, Junmin
    NONLINEAR DYNAMICS, 2021, 103 (03) : 2753 - 2768
  • [37] Finite-time non-fragile boundary feedback control for a class of nonlinear parabolic systems
    Chengzhou Wei
    Junmin Li
    Nonlinear Dynamics, 2021, 103 : 2753 - 2768
  • [38] Robust Finite-Time Control for a Class of Networked Switched Systems Using an Event-Triggered Observer
    Oussama Derouiche
    Djekidel Kamri
    Circuits, Systems, and Signal Processing, 2024, 43 (2) : 821 - 842
  • [39] Robust Finite-Time Control for a Class of Networked Switched Systems Using an Event-Triggered Observer
    Derouiche, Oussama
    Kamri, Djekidel
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2024, 43 (02) : 821 - 842
  • [40] Non-fragile finite-time guaranteed cost fuzzy control for continuous-time nonlinear systems
    Lei Zhang
    Xiang-Yun Wang
    Kun Zhang
    International Journal of Computational Intelligence Systems, 2014, 7 : 129 - 135