Dual‐mode resilient model predictive control for cyber‐physical systems against DoS attacks

In this article, a resilient model predictive control algorithm incorporating a dual‐mode control strategy is proposed for a class of cyber‐physical systems subject to state and input constraints, additive disturbances and denial‐of‐service (DoS) attacks. An adversary aims to disrupt the controller‐...

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Published inInternational journal of robust and nonlinear control Vol. 34; no. 8; pp. 5364 - 5383
Main Authors Yang, Huan, Dai, Li, Xie, Huahui, Cai, Pushen, Xia, Yuanqing
Format Journal Article
LanguageEnglish
Published Bognor Regis Wiley Subscription Services, Inc 25.05.2024
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Abstract In this article, a resilient model predictive control algorithm incorporating a dual‐mode control strategy is proposed for a class of cyber‐physical systems subject to state and input constraints, additive disturbances and denial‐of‐service (DoS) attacks. An adversary aims to disrupt the controller‐to‐actuator channel by deploying adversarial jamming signals. By exploring the prediction uncertainty between a nominal model and an actual model and utilizing a constraint tightening technique, a novel set of constraints is developed, which guarantees robust constraint satisfaction in open‐loop mode caused by DoS attacks. A robust positive invariant set is designed, which allows the control mode to switch from rolling optimization to a state‐feedback control law when the state enters its interior, thus saving computational resources. We explicitly determine a critical duration for DoS attacks and, through theoretical analysis, establish that when the duration of DoS attacks falls below this critical value, the proposed algorithm ensures guaranteed recursive feasibility and robust asymptotic stability. Finally, some comparisons are provided to illustrate the effectiveness of the proposed approach.
AbstractList In this article, a resilient model predictive control algorithm incorporating a dual‐mode control strategy is proposed for a class of cyber‐physical systems subject to state and input constraints, additive disturbances and denial‐of‐service (DoS) attacks. An adversary aims to disrupt the controller‐to‐actuator channel by deploying adversarial jamming signals. By exploring the prediction uncertainty between a nominal model and an actual model and utilizing a constraint tightening technique, a novel set of constraints is developed, which guarantees robust constraint satisfaction in open‐loop mode caused by DoS attacks. A robust positive invariant set is designed, which allows the control mode to switch from rolling optimization to a state‐feedback control law when the state enters its interior, thus saving computational resources. We explicitly determine a critical duration for DoS attacks and, through theoretical analysis, establish that when the duration of DoS attacks falls below this critical value, the proposed algorithm ensures guaranteed recursive feasibility and robust asymptotic stability. Finally, some comparisons are provided to illustrate the effectiveness of the proposed approach.
Author Xia, Yuanqing
Xie, Huahui
Yang, Huan
Dai, Li
Cai, Pushen
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Snippet In this article, a resilient model predictive control algorithm incorporating a dual‐mode control strategy is proposed for a class of cyber‐physical systems...
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SubjectTerms Actuators
Algorithms
Constraint modelling
Control algorithms
Control theory
cyber‐physical systems
Denial of service attacks
Feedback control
Jamming
model predictive control
Predictive control
resilient control
Robustness
Title Dual‐mode resilient model predictive control for cyber‐physical systems against DoS attacks
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