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Observed-Mode-Dependent Nonfragile Control of Networked Control Systems Under Hidden DoS Attacks

Shiyu Jiao, Shengyuan Xu

2023IEEE Transactions on Control of Network Systems15 citationsDOI

Abstract

This article develops a methodology on observed-mode-dependent nonfragile control for networked control systems subject to denial-of-service (DoS) attacks, which takes the strong concealment of attack behavior into account. To describe complex switching phenomenon between different forms of attacks that the adversary may launch on communication channels, the semi-Markov chain (SMC) is introduced. DoS attacks with a stealth characteristic are analyzed from a hidden semi-Markov jump systems perspective by constructing a double-layer stochastic process consisting of an SMC and an observed mode sequence. With the aid of emission probability, an observed-mode-dependent nonfragile controller is designed, which can still stabilize the system even if actual attack modes are unavailable. By utilizing the Lyapunov function that depends on actual attack modes and observed ones, sufficient conditions to ensure the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula> -error mean square stability of the closed-loop system is deduced. Eventually, a simulation related to the mass-spring-damper system with a single channel and an example of the unmanned ground vehicle with two channels are studied, both of which demonstrate the feasibility and validity.

Topics & Concepts

Control theory (sociology)Mode (computer interface)Computer scienceController (irrigation)Lyapunov functionControl systemMarkov chainDenial-of-service attackMarkov processControl (management)MathematicsEngineeringArtificial intelligencePhysicsBiologyNonlinear systemMachine learningStatisticsThe InternetWorld Wide WebOperating systemAgronomyQuantum mechanicsElectrical engineeringSmart Grid Security and ResilienceNetwork Security and Intrusion DetectionInfrastructure Resilience and Vulnerability Analysis
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