LMI-based adaptive control for uncertain polytopic systems
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Universidade Federal de Minas Gerais
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Despite 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.
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Engenharia Elétrica, Liapunov, Funções de, Equações diferenciais, Sistemas difusos, Sistemas especialistas (Computação)
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Sistemas Incertos, LMIs, Estabilidade de Sistemas Não Lineares, Controle, Controle de Processos, Symmetric matrices , Lyapunov methods , PD control , Robustness , Uncertain systems , Closed loop systems , Adaptive control, Adaptive 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
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https://ieeexplore.ieee.org/document/7798753