Event-triggered control of Takagi-Sugeno fuzzy systems under deception attacks

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dc.creatorMárcia L. C. Peixoto
dc.creatorPedro H. S. Coutinho
dc.creatorIury Bessa
dc.creatorPaulo Sérgio Pereira Pessim
dc.creatorReinaldo M. Palhares
dc.date.accessioned2025-05-29T13:44:58Z
dc.date.accessioned2025-09-09T00:27:29Z
dc.date.available2025-05-29T13:44:58Z
dc.date.issued2023
dc.identifier.doi10.1002/rnc.6760
dc.identifier.issn10991239
dc.identifier.urihttps://hdl.handle.net/1843/82610
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.rightsAcesso Restrito
dc.subjectModelos matemáticos
dc.subjectInternet. Medidas de segurança
dc.subject.otherNetworked control systems (NCSs) are systems where a communication network is used in the data exchange between their elements, namely the actuators, sensors, and controllers. While the NCSs are becoming popular due to the advances in internet resources and the convenience of the operation and maintenance, it raises new challenges and threats which are inherent to those systems, such as network-induced delays, data packet dropouts, the limited bandwidth of communication networks, disorder, and the vulnerability to cyber-attacks. All those issues are discussed in Reference 1 and references therein.
dc.titleEvent-triggered control of Takagi-Sugeno fuzzy systems under deception attacks
dc.typeArtigo de periódico
local.citation.epage7487
local.citation.issue13
local.citation.spage7471
local.citation.volume33
local.description.resumoThis article handles the problem of periodic event-triggered control co-design for the stabilization of Takagi-Sugeno fuzzy models subject to stochastic deception attacks whose occurrence follows a given Bernoulli distribution. A novel delay-dependent condition is presented to simultaneously design the event-triggering mechanism and the state-feedback controller to ensure the local mean-square asymptotic stability of the closed-loop system. The co-design condition is derived as linear matrix inequalities by considering Lyapunov–Krasovskii stability arguments. In addition, an optimization procedure is provided to estimate an enlarged set of admissible initial conditions and the corresponding ultimate bound within the validity domain of the fuzzy model. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed approach.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://onlinelibrary.wiley.com/doi/full/10.1002/rnc.6760

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