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Parameter uncertainty modeling using the multidimensional principal curves / Sepasi, M. in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 132 N° 5 (Septembre 2010) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 132 N° 5 (Septembre 2010) . - 07 p. Titre : Parameter uncertainty modeling using the multidimensional principal curves Type de document : texte imprimé Auteurs : Sepasi, M., Auteur ; Sassani, F., Auteur ; Nagamune, R., Auteur Année de publication : 2010 Article en page(s) : 07 p. Note générale : Systèmes dynamiques Langues : Anglais (eng) Mots-clés : Parameter  uncertainty  modeling  Nonlinear  principal  component  analysis  Parameter  variation  Multidimensional  principal  curve Index. décimale : 629.8 Résumé : This paper proposes a technique to model uncertainties associated with linear time-invariant systems. It is assumed that the uncertainties are only due to parametric variations caused by independent uncertain variables. By assuming that a set of a finite number of rational transfer functions of a fixed order is given, as well as the number of independent uncertain variables that affect the parametric uncertainties, the proposed technique seeks an optimal parametric uncertainty model as a function of uncertain variables that explains the set of transfer functions. Finding such an optimal parametric uncertainty model is formulated as a noncovex optimization problem, which is then solved by a combination of a linear matrix inequality and a nonlinear optimization technique. To find an initial condition for solving this nonconvex problem, the nonlinear principal component analysis based on the multidimensional principal curve is employed. The effectiveness of the proposed technique is verified through both illustrative and practical examples. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013200 [...] [article] Parameter uncertainty modeling using the multidimensional principal curves [texte imprimé] / Sepasi, M., Auteur ; Sassani, F., Auteur ; Nagamune, R., Auteur . - 2010 . - 07 p. Systèmes dynamiques Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 132 N° 5 (Septembre 2010) . - 07 p. Mots-clés : Parameter  uncertainty  modeling  Nonlinear  principal  component  analysis  Parameter  variation  Multidimensional  principal  curve Index. décimale : 629.8 Résumé : This paper proposes a technique to model uncertainties associated with linear time-invariant systems. It is assumed that the uncertainties are only due to parametric variations caused by independent uncertain variables. By assuming that a set of a finite number of rational transfer functions of a fixed order is given, as well as the number of independent uncertain variables that affect the parametric uncertainties, the proposed technique seeks an optimal parametric uncertainty model as a function of uncertain variables that explains the set of transfer functions. Finding such an optimal parametric uncertainty model is formulated as a noncovex optimization problem, which is then solved by a combination of a linear matrix inequality and a nonlinear optimization technique. To find an initial condition for solving this nonconvex problem, the nonlinear principal component analysis based on the multidimensional principal curve is employed. The effectiveness of the proposed technique is verified through both illustrative and practical examples. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013200 [...]