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dc.contributor.authorLi, Jines_ES
dc.contributor.authorTan, Yuejines_ES
dc.contributor.authorLiao, Liangcaies_ES
dc.date.accessioned2007-03-12T15:21:21Zes_ES
dc.date.accessioned2010-09-07T16:32:53Zes_ES
dc.date.accessioned2011-03-10T14:33:27Z-
dc.date.available2007-03-12T15:21:21Zes_ES
dc.date.available2010-09-07T16:32:53Zes_ES
dc.date.available2011-03-10T14:33:27Z-
dc.date.issued2007-03-12T15:21:21Zes_ES
dc.identifier.urihttp://bibdigital.epn.edu.ec/handle/15000/9309es_ES
dc.description.abstractIn this paper, a module-oriented automatic differentiation (MAD) approach is presented based on traditional automatic differentiation algorithms. This approach can well exploit the sparsity of the model by partitioning it into a series of sequential modules and choosing the best differentiation algorithm for each module accordingly. Numerical results show that for nonlinear system, module-oriented automatic differentiation can calculate the Lie derivatives and Jacobians efficiently.es_ES
dc.language.isoenges_ES
dc.rightsopenAccess-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectSISTEMAS DE CONTROL NO LINEALes_ES
dc.subject.otherNONLINEAR CONTROL SYSTEMSes_ES
dc.titleModule-oriented automatic differentiation in nonlinear controles_ES
dc.typeArticlees_ES
Aparece en las colecciones: 2005 International Conference on Industrial Electronics and Control Applications (FIEE)

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