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Sliding Mode Control for Sampled-Data Systems Subject to Deception Attacks: Handling Randomly Perturbed Sampling Periods

Zhiru Cao, Zidong Wang, Yugang Niu, Jun Song, Hongjian Liu

2022IEEE Transactions on Cybernetics49 citationsDOI

Abstract

In this article, the sliding mode control problem is addressed for a class of sampled-data systems subject to deception attacks. The sampling periods undergo component-wise random perturbations that are governed by a Markovian chain. The component of the sampled output is transmitted via an individual communication channel that is vulnerable to deception attacks, and Bernoulli-distributed stochastic variables are utilized to characterize the random occurrence of the deception attacks initiated by the adversaries. A sliding mode controller is designed to drive the state into the sliding domain around the specified sliding surface, and sufficient conditions are derived to guarantee the exponentially ultimate boundedness of the resultant closed-loop system in the mean-square sense. Furthermore, an optimization problem is established to pursue locally optimal control performance. Finally, a simulation example is given to verify the effectiveness and advantages of the developed controller design approach.

Topics & Concepts

DeceptionControl theory (sociology)Bernoulli's principleController (irrigation)Computer scienceBernoulli distributionMode (computer interface)Sliding mode controlComponent (thermodynamics)Control (management)Random variableMathematicsEngineeringLawArtificial intelligenceStatisticsNonlinear systemAgronomyQuantum mechanicsPolitical sciencePhysicsBiologyAerospace engineeringOperating systemThermodynamicsSmart Grid Security and ResilienceStability and Control of Uncertain SystemsDistributed Control Multi-Agent Systems
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