LMI-based adaptive control for uncertain polytopic systems

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dc.creatorVictor Costa da Silva Campos
dc.creatorAnh-Tu Nguyen
dc.creatorReinaldo Martinez Palhares
dc.date.accessioned2025-03-24T14:25:09Z
dc.date.accessioned2025-09-08T23:23:06Z
dc.date.available2025-03-24T14:25:09Z
dc.date.issued2016
dc.identifier.doi10.1109/CDC.2016.7798753
dc.identifier.urihttps://hdl.handle.net/1843/80848
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.rightsAcesso Restrito
dc.subjectEngenharia Elétrica
dc.subjectLiapunov, Funções de
dc.subjectEquações diferenciais
dc.subjectSistemas difusos
dc.subjectSistemas especialistas (Computação)
dc.subject.otherSistemas Incertos
dc.subject.otherLMIs
dc.subject.otherEstabilidade de Sistemas Não Lineares
dc.subject.otherControle
dc.subject.otherControle de Processos
dc.subject.otherSymmetric matrices , Lyapunov methods , PD control , Robustness , Uncertain systems , Closed loop systems , Adaptive control
dc.subject.otherAdaptive Control , Polytopic Systems , Optimal Control , Set Of Conditions , Fundamental Differences , Membership Function , Fuzzy System , Linear Matrix Inequalities , Uncertain Systems , Adaptive Law , Adaptive Control Law , State Space , Symmetric Matrix , Parameter Uncertainty , Lyapunov Function , State-space Model , Convex Combination , Linear Law , Quadratic Lyapunov Function , Linear Matrix Inequality Conditions , Linear Parameter Varying
dc.titleLMI-based adaptive control for uncertain polytopic systems
dc.typeArtigo de evento
local.citation.epage3227
local.citation.spage3222
local.description.resumoDespite the similarities between polytopic uncertain systems and Takagi-Sugeno fuzzy models, there is a fundamental difference: the exact knowledge of the linear systems weighting functions (also known as membership functions in the fuzzy systems literature). This knowledge is usually incorporated into fuzzy control laws, which allows for less conservative controllers. This work proposes a novel set of LMI synthesis conditions which when feasible guarantees that an adaptive control law, mimicking a fuzzy control law, asymptotically stabilizes the uncertain polytopic system. A numerical example is presented to demonstrate the effectiveness of the proposed control law.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://ieeexplore.ieee.org/document/7798753

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