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

• Published in: IEEE transactions on cybernetics Vol. 53; no. 11; pp. 1 - 14
• Main Authors: Cao, Zhiru, Wang, Zidong, Niu, Yugang, Song, Jun, Liu, Hongjian
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.11.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Closed loops; Control systems design; Controllers; Data systems; Feedback control; Markov chains; Markovian model; Nonuniform sampling; Optimal control; Optimization; Perturbation; randomly occurring deception attacks; randomly perturbed sampling periods (RPSPs); Sampled data systems; Sliding mode control; sliding mode control (SMC); Stochastic processes; Symmetric matrices; Time measurement
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2022.3202486

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.