Protocol-Based Control for Discrete-Time Positive Markovian Switching Models With Deception Attacks

被引:5
|
作者
Qi, Wenhai [1 ,2 ]
Yi, Yanjing [1 ]
Park, Ju H. [3 ]
Yan, Huaicheng [4 ]
Cheng, Jun [5 ]
机构
[1] Qufu Normal Univ, Sch Engn, Rizhao 276826, Peoples R China
[2] Chengdu Univ, Sch Informat Sci & Engn, Chengdu 610106, Peoples R China
[3] Yeungnam Univ, Dept Elect Engn, Kyongsan 38541, South Korea
[4] East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China
[5] Guangxi Normal Univ, Coll Math & Stat, Guilin 541006, Peoples R China
基金
中国国家自然科学基金; 新加坡国家研究基金会;
关键词
Actuators; Control systems; Protocols; Cyberattack; Switches; Stochastic processes; Stability criteria; Markovian switching models; deception attacks; event-triggered protocol; stochastic stability; SYSTEMS;
D O I
10.1109/TCSII.2022.3220019
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This brief investigates the problem of protocol-based control for positive Markovian switching models subject to actuator faults and deception attacks. Bernoulli distribution is adopted to depict random deception attacks. Considering the positivity of Markovian switching models, an event-triggered protocol is constructed based on a 1-norm to be related to the error signal and the state signal. In order to handle actuator faults and random cyber attacks, exponentially stochastic stability conditions are established under the event-triggered protocol by developing a linear copositive Lyapunov function approach. Furthermore, a non-fragile control law combined with the event-triggered protocol is proposed such that exponential stochastic stability of the corresponding system is achieved on the basis of matrix decomposition strategy and linear programming. Finally, a data communication network model is provided to demonstrate the effectiveness of the proposed controller design.
引用
收藏
页码:1485 / 1489
页数:5
相关论文
共 50 条
  • [1] Protocol-based SMC for singularly perturbed systems with switching parameters and deception attacks
    Shen, Chuangchun
    Xu, Jiangming
    Cheng, Jun
    Yan, Huaicheng
    Cao, Jinde
    INFORMATION SCIENCES, 2024, 679
  • [2] Protocol-Based Fuzzy Control of Networked Systems Under Joint Deception Attacks
    Gao, Xiaobin
    Deng, Feiqi
    Su, Chun-Yi
    Zeng, Pengyu
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2023, 31 (03) : 1052 - 1063
  • [3] Security Control for Discrete-Time Stochastic Nonlinear Systems Subject to Deception Attacks
    Ding, Derui
    Wang, Zidong
    Han, Qing-Long
    Wei, Guoliang
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2018, 48 (05): : 779 - 789
  • [4] Model Predictive Control of Discrete-time Markovian Jump Positive Systems
    Mehrivash, Hamed
    Hadavand, Ehsan
    Shafiei, Mohammad Hosein
    Zarei, Jafar
    26TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE 2018), 2018, : 834 - 839
  • [5] Asynchronous H∞ Control for Positive Discrete-time Markovian Jump Systems
    Hui Shang
    Wenhai Qi
    Guangdeng Zong
    International Journal of Control, Automation and Systems, 2020, 18 : 431 - 438
  • [6] Asynchronous H∞ Control for Positive Discrete-time Markovian Jump Systems
    Shang, Hui
    Qi, Wenhai
    Zong, Guangdeng
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2020, 18 (02) : 431 - 438
  • [7] State-Estimator-Based Asynchronous Repetitive Control of Discrete-Time Markovian Switching Systems
    Liu, Xinghua
    Ma, Guoqi
    Pagilla, Prabhakar R.
    Ge, Shuzhi Sam
    COMPLEXITY, 2020, 2020 (2020)
  • [8] The safety region-based model predictive control for discrete-time systems under deception attacks
    Xu, Yang
    Yuan, Yuan
    Yang, Hongjiu
    Zhou, Dalin
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2021, 52 (10) : 2144 - 2160
  • [9] Protocol-based collaborative design for discrete-time switched systems with sojourn probabilities
    Zhu, Di
    Wei, Guoliang
    Li, Jiajia
    Ding, Derui
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2020, 30 (18) : 8044 - 8059
  • [10] Protocol-based fault detection for discrete-time memristive neural networks with effect
    Cheng, Jun
    Lin, An
    Cao, Jinde
    Qiu, Jianlong
    Qi, Wenhai
    INFORMATION SCIENCES, 2022, 615 : 118 - 135