2018
DOI: 10.1016/j.asej.2018.03.001
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State-feedback control of robot manipulators using polytopic LPV modelling with fuzzy-clustering

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Cited by 5 publications
(2 citation statements)
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“…The LPV framework has become a well-accepted approach to extend LTI schemes for control and estimation to non-linear systems via the non-linear embedding of the non-linearities in the varying parameters (avoiding linearization) and LMIs (as e.g. see Kazemi & Jabali, 2018;Marx, Ichalal, Ragot, Maquin, & Mammar, 2019;Morato, Sename, Dugard, & Nguyen, 2019). Note that, in the last decades, several control and estimation strategies have been designed on the basis of LMIs, because it is not difficult to formulate those problems by using an LMI framework.…”
Section: Introductionmentioning
confidence: 99%
“…The LPV framework has become a well-accepted approach to extend LTI schemes for control and estimation to non-linear systems via the non-linear embedding of the non-linearities in the varying parameters (avoiding linearization) and LMIs (as e.g. see Kazemi & Jabali, 2018;Marx, Ichalal, Ragot, Maquin, & Mammar, 2019;Morato, Sename, Dugard, & Nguyen, 2019). Note that, in the last decades, several control and estimation strategies have been designed on the basis of LMIs, because it is not difficult to formulate those problems by using an LMI framework.…”
Section: Introductionmentioning
confidence: 99%
“…Os sistemas LPV, como exposto em Shamma (1988), são sistemas não lineares descritos por modelos matemáticos lineares, nos quais os coeficientes variam em função de um parâmetro de scheduling. Nasúltimas duas décadas, muitos artigos foram publicados sobre os métodos de identificação e projeto de controladores LPV para diferentes aplicações industriais: controle do amortecimento de oscilações mecânicos em sistemas de geração (Nogueira et al, 2018), motores automotivos em M. Morato et al (2019), robótica em Kazemi and Jabali (2018), turbinas em Perez-Estrada et al (2018), entre outros.…”
Section: Introductionunclassified