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author:

Qi, Y. (Qi, Y..) [1] | Ji, M. (Ji, M..) [2] | Tang, Y. (Tang, Y..) [3] | Geng, H. (Geng, H..) [4] | Qu, Z. (Qu, Z..) [5] | Guo, S. (Guo, S..) [6]

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Scopus

Abstract:

This paper studies the event-triggered control for uncertain switched systems under injection attacks. An adaptive event-triggered control method for neural network–approximated switched systems (NNA-SSs) is proposed. The main works are as follows: First, a neural network is introduced to approximate the uncertain nonlinear item of the systems. Second, the observer-based adaptive event-triggering (OB-AET) strategy is designed to efficiently utilize communication and computing resources. Furthermore, the closed-loop switched systems considering injection attacks are established. By utilizing the Lyapunov function method and average dwell time technique, sufficient conditions for the exponential stability of the closed-loop switched systems are given. Accordingly, the gains of the state feedback controllers and observers are solved. Finally, simulation examples are given to verify the effectiveness of the proposed method. © The Author(s) 2024.

Keyword:

average dwell time technique false data injection attacks multiple Lyapunov functions observer-based adaptive event-triggering Switched systems uncertainty approximated by neural networks

Community:

  • [ 1 ] [Qi Y.]School of Automation, Shenyang Aerospace University, China
  • [ 2 ] [Qi Y.]College of Electrical Engineering and Automation, Fuzhou University, China
  • [ 3 ] [Ji M.]School of Automation, Shenyang Aerospace University, China
  • [ 4 ] [Tang Y.]School of Automation, Shenyang Aerospace University, China
  • [ 5 ] [Geng H.]School of Automation, Shenyang Aerospace University, China
  • [ 6 ] [Qu Z.]School of Automation, Shenyang Aerospace University, China
  • [ 7 ] [Guo S.]School of Automation, Shenyang Aerospace University, China

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Source :

Transactions of the Institute of Measurement and Control

ISSN: 0142-3312

Year: 2024

Issue: 13

Volume: 46

Page: 2627-2635

1 . 7 0 0

JCR@2023

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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