A tensor product model transformation approach to the discretization of uncertain linear systems
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Universidade Federal de Minas Gerais
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Artigo de periódico
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Resumo
Most of the discretization approaches for uncertain linear systems make use of
the series representation of the matrix exponential function and truncate the summation
after a certain order. This usually leads to discrete-time uncertain polytopic models
described by polynomial matrices with multiple indexes, which usually means that the
higher the order used in the approximation, the higher the number of linear matrix
inequalities (LMI) needed. This work, instead, proposes an approach based on a grid of the
possible values for the matrix exponential function and an application of the tensor product
model transformation technique to find a suitable polytopic model. Numerical examples are
presented to illustrate the advantages and the applicability of the proposed technique.
Abstract
Assunto
Sistemas não lineares, Modelos matemáticos
Palavras-chave
LMIs, Discretization, Uncertainty, Tensor-Product, Model Transformation, Ever since efficient interior-point methods for semi-definite programming made the use of Linear Matrix Inequalities (LMIs) computationally tractable, it has been extensively used for the robust control of linear systems
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https://acta.uni-obuda.hu/Campos_Sathler-Vianna_Braga_82.pdf