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Finite-time control for discrete-time nonlinear Markov switching LPV systems with DoS attacks

•Compared with Markov switching LPV systems in line with the ideal network environment [39,41,63,64], the aperiodic DoS attacks are introduced into discrete-time Markov switching LPV systems for the first time, which is more general.•Different from Markov switching LPV systems over an infinite time...

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Bibliographic Details
Published in:Applied mathematics and computation 2023-04, Vol.443, p.127783, Article 127783
Main Authors: Xu, Qiyi, Zhang, Ning, Qi, Wenhai
Format: Article
Language:English
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Summary:•Compared with Markov switching LPV systems in line with the ideal network environment [39,41,63,64], the aperiodic DoS attacks are introduced into discrete-time Markov switching LPV systems for the first time, which is more general.•Different from Markov switching LPV systems over an infinite time interval [38–41,63,64], according to that whether the systems are under DoS attacks or not, sufficient conditions are proposed to ensure the finite-time stability of the closed-loop system by using multiple Lyapunov function method and iterative technique.•An appropriate feedback controller is designed to make the underlying system finite-time stable in standard framework. This work studies the finite-time control problem for discrete-time nonlinear Markov switching linear parameter varying (LPV) systems with denial-of-service (DoS) attacks. The aperiodic DoS attacks are introduced into the systems with partially unknown transition probabilities. First, considering the characteristics of aperiodic DoS attacks, an appropriate feedback controller is designed according to that whether it is attacked or not. Furthermore, the finite-time stability criteria of closed-loop system are derived by means of iterative technique and multiple Lyapunov functions. Finally, a turbofan engine model is taken as an example to verify the effectiveness and feasibility of the proposed finite-time control method.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2022.127783