Input-to-State Stabilization for Markov Jump Systems With Dynamic Quantization and Multimode Injection Attacks

Zhou, Jianping; Dong, Jingjing; Xu, Shengyuan; Ahn, Choon Ki

doi:10.1109/tsmc.2023.3344869

IEEE Trans. Syst. Man Cybern, Syst.

2024

DOI: 10.1109/tsmc.2023.3344869

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Input-to-State Stabilization for Markov Jump Systems With Dynamic Quantization and Multimode Injection Attacks

Jianping Zhou,

Jingjing Dong,

Shengyuan Xu

et al.

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2024

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Round-robin scheduling protocol-based stabilization for discrete-time Markov jumping neural networks

Gao

2024

AIP Advances

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This paper focuses on the stabilization problem of discrete-time Markov jumping neural networks (DMJNNs) under communication constraints between the actuators and the remote controller. To reduce the communication burden, a round-robin scheduling protocol is introduced to allocate the right to a single actuator to exclusively use the communication channel at a given time while ensuring that multiple nodes can take turns to occupy the channel for signal transmission. Two criteria for stochastic analysis of the closed-loop network model are presented based on different assumptions of the activation functions. Then, numerically tractable design methods for the required controller gains are developed. Finally, the three-mode DMJNN model is used as an example to illustrate the complementarity and effectiveness of the presented analysis results and design methods.

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Round-robin scheduling protocol-based stabilization for discrete-time Markov jumping neural networks

Gao

2024

AIP Advances

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Dissipative control for singular Takagi-Sugeno fuzzy systems with random actuator failures

Zhang,

He,

et al. 2024

MFC

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Input-to-State Stabilization for Markov Jump Systems With Dynamic Quantization and Multimode Injection Attacks

Cited by 2 publications

References 50 publications

Round-robin scheduling protocol-based stabilization for discrete-time Markov jumping neural networks

Round-robin scheduling protocol-based stabilization for discrete-time Markov jumping neural networks

Dissipative control for singular Takagi-Sugeno fuzzy systems with random actuator failures

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