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• W2918781369 startingPage "138" @default.
• W2918781369 abstract "Industrial cyber–physical systems generally suffer from the malicious attacks and unmatched perturbation, and thus the security issue is always the core research topic in the related fields. This paper proposes a novel intelligent secure control scheme, which integrates optimal control theory, zero-sum game theory, reinforcement learning and neural networks. First, the secure control problem of the compromised system is converted into the zero-sum game issue of the nominal auxiliary system, and then both policy-iteration-based and value-iteration-based adaptive dynamic programming methods are introduced to solve the Hamilton–Jacobi–Isaacs equations. The proposed secure control scheme can mitigate the effects of actuator attacks and unmatched perturbation, and stabilize the compromised cyber–physical systems by tuning the system performance parameters, which is proved through the Lyapunov stability theory. Finally, the proposed approach is applied to the Quanser helicopter to verify the effectiveness." @default.
• W2918781369 created "2019-03-11" @default.
• W2918781369 creator A5013219172 @default.
• W2918781369 creator A5015547077 @default.
• W2918781369 creator A5016971514 @default.
• W2918781369 date "2020-09-01" @default.
• W2918781369 modified "2023-10-17" @default.
• W2918781369 title "Critic-only adaptive dynamic programming algorithms’ applications to the secure control of cyber–physical systems" @default.
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• W2918781369 doi "https://doi.org/10.1016/j.isatra.2019.02.012" @default.
• W2918781369 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30853105" @default.
• W2918781369 hasPublicationYear "2020" @default.
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