Event-triggered stochastic model predictive control based on distributionally robust optimization approach for network control systems under DoS attacks

In this paper, we propose a novel event-triggered stochastic model predictive control (SMPC) algorithm based on distributionally robust optimization (DRO) for network control systems (NCSs) that are affected by additive disturbances and Denial-of-Service (DoS) attacks. The event-triggered mechanism...

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Published inSignal processing Vol. 238; p. 110182
Main Authors Chen, Yadong, Wan, Chao, Cheng, Peng
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.01.2026
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Abstract In this paper, we propose a novel event-triggered stochastic model predictive control (SMPC) algorithm based on distributionally robust optimization (DRO) for network control systems (NCSs) that are affected by additive disturbances and Denial-of-Service (DoS) attacks. The event-triggered mechanism is designed to reduce sampling times, communication costs, and computational demands while maintaining performance. By converting chance constraints into second-order cone (SOC) constraints, the algorithm effectively addresses disturbances with limited prior knowledge, utilizing accessible first and second moments. The proposed event-triggered DR-SMPC (ETM-DR-SMPC) has longer sampling intervals than periodic sampling DR-SMPC (PDR-SMPC). Compared to self-triggered SMPC (SSMPC), ETM-DR-SMPC has longer sampling intervals, less computation, better performance and fewer constraint violations. It also has better performance and longer sampling intervals than event-triggered robust model predictive control (ETM-RMPC). Furthermore, we demonstrate the exponential mean square stability of ETM-DR-SMPC for the first time and the recursive feasibility of ETM-DR-SMPC is guaranteed. Numerical simulations validate the effectiveness of the proposed algorithm. •In this paper, we demonstrate for the first time the exponentially mean square stability of NCSs with SMPC in the framework of DRO approach.•We establish ETM-DR-SMPC algorithm that incorporates the aforementioned constraint, disturbances, and DoS attacks for the first time.•The event-triggered control is introduced into distributed robust optimization SMPC (DR-SMPC) and we design a stochastic event-triggered function.•We propose ETM-DR-SMPC compensation strategy for NCSs which subject to DoS attacks.
AbstractList In this paper, we propose a novel event-triggered stochastic model predictive control (SMPC) algorithm based on distributionally robust optimization (DRO) for network control systems (NCSs) that are affected by additive disturbances and Denial-of-Service (DoS) attacks. The event-triggered mechanism is designed to reduce sampling times, communication costs, and computational demands while maintaining performance. By converting chance constraints into second-order cone (SOC) constraints, the algorithm effectively addresses disturbances with limited prior knowledge, utilizing accessible first and second moments. The proposed event-triggered DR-SMPC (ETM-DR-SMPC) has longer sampling intervals than periodic sampling DR-SMPC (PDR-SMPC). Compared to self-triggered SMPC (SSMPC), ETM-DR-SMPC has longer sampling intervals, less computation, better performance and fewer constraint violations. It also has better performance and longer sampling intervals than event-triggered robust model predictive control (ETM-RMPC). Furthermore, we demonstrate the exponential mean square stability of ETM-DR-SMPC for the first time and the recursive feasibility of ETM-DR-SMPC is guaranteed. Numerical simulations validate the effectiveness of the proposed algorithm. •In this paper, we demonstrate for the first time the exponentially mean square stability of NCSs with SMPC in the framework of DRO approach.•We establish ETM-DR-SMPC algorithm that incorporates the aforementioned constraint, disturbances, and DoS attacks for the first time.•The event-triggered control is introduced into distributed robust optimization SMPC (DR-SMPC) and we design a stochastic event-triggered function.•We propose ETM-DR-SMPC compensation strategy for NCSs which subject to DoS attacks.
ArticleNumber 110182
Author Wan, Chao
Chen, Yadong
Cheng, Peng
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Keywords DoS attacks
Event-triggered control
Distributionally robust optimization(DRO)
Stochastic model predictive control(SMPC)
Language English
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Snippet In this paper, we propose a novel event-triggered stochastic model predictive control (SMPC) algorithm based on distributionally robust optimization (DRO) for...
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elsevier
SourceType Index Database
Publisher
StartPage 110182
SubjectTerms Distributionally robust optimization(DRO)
DoS attacks
Event-triggered control
Stochastic model predictive control(SMPC)
Title Event-triggered stochastic model predictive control based on distributionally robust optimization approach for network control systems under DoS attacks
URI https://dx.doi.org/10.1016/j.sigpro.2025.110182
Volume 238
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