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Détail de l'auteur
Auteur Finch, John W.
Documents disponibles écrits par cet auteur
Affiner la rechercheMultivariable self-tuning control of a turbine generator system / Zachariah, K. J. in IEEE transactions on energy conversion, Vol. 24 N° 2 (Juin 2009)
[article]
in IEEE transactions on energy conversion > Vol. 24 N° 2 (Juin 2009) . - pp. 406 - 414
Titre : Multivariable self-tuning control of a turbine generator system Type de document : texte imprimé Auteurs : Zachariah, K. J., Auteur ; Finch, John W., Auteur ; Mohammad Farsi, Auteur Année de publication : 2009 Article en page(s) : pp. 406 - 414 Note générale : energy energy Langues : Anglais (eng) Mots-clés : Predictive control; self-adjusting systems; turbogenerators; voltage regulators Résumé : Results from a collaborative research and development program devoted to turbine generator (TG) control are described. Digital self-tuning excitation controllers were designed for a generator during the initial phase of the project, with the design subsequently extended to cover multivariable control of the TG, which is the topic of this paper. Simulations and tests on a laboratory-scale machine have been accomplished successfully and a prototype multivariable self-tuning controller has been built. A set of typical results is given, covering responses to fault conditions of the power system. The multivariable self-tuning controller is shown to have good potential for commercial use for the TG. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4957573&sortType%3Das [...] [article] Multivariable self-tuning control of a turbine generator system [texte imprimé] / Zachariah, K. J., Auteur ; Finch, John W., Auteur ; Mohammad Farsi, Auteur . - 2009 . - pp. 406 - 414.
energy energy
Langues : Anglais (eng)
in IEEE transactions on energy conversion > Vol. 24 N° 2 (Juin 2009) . - pp. 406 - 414
Mots-clés : Predictive control; self-adjusting systems; turbogenerators; voltage regulators Résumé : Results from a collaborative research and development program devoted to turbine generator (TG) control are described. Digital self-tuning excitation controllers were designed for a generator during the initial phase of the project, with the design subsequently extended to cover multivariable control of the TG, which is the topic of this paper. Simulations and tests on a laboratory-scale machine have been accomplished successfully and a prototype multivariable self-tuning controller has been built. A set of typical results is given, covering responses to fault conditions of the power system. The multivariable self-tuning controller is shown to have good potential for commercial use for the TG. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4957573&sortType%3Das [...] Sensorless control of induction motor drives at very low and zero speeds using neural network flux observers / Gadoue, Shady M. in IEEE transactions on industrial electronics, Vol. 56 N° 8 (Août 2009)
[article]
in IEEE transactions on industrial electronics > Vol. 56 N° 8 (Août 2009) . - pp. 3029 - 3039
Titre : Sensorless control of induction motor drives at very low and zero speeds using neural network flux observers Type de document : texte imprimé Auteurs : Gadoue, Shady M., Auteur ; Giaouris, Damian, Auteur ; Finch, John W., Auteur Article en page(s) : pp. 3029 - 3039 Note générale : Génie électrique Langues : Anglais (eng) Mots-clés : Flux estimation Induction motor Model reference adaptive system (MRAS) Neural networks (NNs) Sensorless control Résumé : A new method is described which considerably improves the performance of rotor flux model reference adaptive system (MRAS)-based sensorless drives in the critical low and zero speed regions of operation. It is applied to a vector-controlled induction motor drive and is experimentally verified. The new technique uses an artificial neural network (NN) as a rotor flux observer to replace the conventional voltage model. This makes the reference model free of pure integration and less sensitive to stator resistance variations. This is a radically different way of applying NNs to MRAS schemes. The data for training the NN are obtained from experimental measurements based on the current model avoiding voltage and flux sensors. This has the advantage of considering all drive nonlinearities. Both open- and closed-loop sensorless operations for the new scheme are investigated and compared with the conventional MRAS speed observer. The experimental results show great improvement in the speed estimation performance for open- and closed-loop operations, including zero speed. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5071300 [article] Sensorless control of induction motor drives at very low and zero speeds using neural network flux observers [texte imprimé] / Gadoue, Shady M., Auteur ; Giaouris, Damian, Auteur ; Finch, John W., Auteur . - pp. 3029 - 3039.
Génie électrique
Langues : Anglais (eng)
in IEEE transactions on industrial electronics > Vol. 56 N° 8 (Août 2009) . - pp. 3029 - 3039
Mots-clés : Flux estimation Induction motor Model reference adaptive system (MRAS) Neural networks (NNs) Sensorless control Résumé : A new method is described which considerably improves the performance of rotor flux model reference adaptive system (MRAS)-based sensorless drives in the critical low and zero speed regions of operation. It is applied to a vector-controlled induction motor drive and is experimentally verified. The new technique uses an artificial neural network (NN) as a rotor flux observer to replace the conventional voltage model. This makes the reference model free of pure integration and less sensitive to stator resistance variations. This is a radically different way of applying NNs to MRAS schemes. The data for training the NN are obtained from experimental measurements based on the current model avoiding voltage and flux sensors. This has the advantage of considering all drive nonlinearities. Both open- and closed-loop sensorless operations for the new scheme are investigated and compared with the conventional MRAS speed observer. The experimental results show great improvement in the speed estimation performance for open- and closed-loop operations, including zero speed. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5071300