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Neurofuzzy power system stabilizer / Chaturvedi, D. K. in IEEE transactions on energy conversion, Vol. 23 n°3 (Septembre 2008) 

Public ISBD [article]  in IEEE transactions on energy conversion > Vol. 23 n°3 (Septembre 2008) . - pp. 887 - 894 Titre : Neurofuzzy power system stabilizer Type de document : texte imprimé Auteurs : Chaturvedi, D. K., Auteur ; Malik, O. P., Auteur Année de publication : 2008 Article en page(s) : pp. 887 - 894 Note générale : Energy conversion Langues : Anglais (eng) Mots-clés : Control  engineering  computing;  fuzzy  control;  inference  mechanisms;  neurocontrollers;  power  engineering  computing;  power  system  control;  power  system  stability Résumé : An adaptive fuzzy logic power system stabilizer (AFPSS) consisting of a generalized neuron (GN)-based predictor and a fuzzy logic controller (FLC) is described. The inference mechanism of the FLC is represented by a rule-base and a database. Two parameters, decided on the basis of the GN-predictor output and the current system conditions, are used to tune the AFPSS. This mechanism of tuning makes the fuzzy logic-based power system stabilizer adaptive to changes in the operating conditions. Therefore, variation in the system response, under a wide range of operating conditions, is less compared to the system response with a fixed-parameter conventional PSS. The performance of the AFPSS has been tested by simulation and experimental studies. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4603061&sortType%3Das [...] [article] Neurofuzzy power system stabilizer [texte imprimé] / Chaturvedi, D. K., Auteur ; Malik, O. P., Auteur . - 2008 . - pp. 887 - 894. Energy conversion Langues : Anglais (eng) in IEEE transactions on energy conversion > Vol. 23 n°3 (Septembre 2008) . - pp. 887 - 894 Mots-clés : Control  engineering  computing;  fuzzy  control;  inference  mechanisms;  neurocontrollers;  power  engineering  computing;  power  system  control;  power  system  stability Résumé : An adaptive fuzzy logic power system stabilizer (AFPSS) consisting of a generalized neuron (GN)-based predictor and a fuzzy logic controller (FLC) is described. The inference mechanism of the FLC is represented by a rule-base and a database. Two parameters, decided on the basis of the GN-predictor output and the current system conditions, are used to tune the AFPSS. This mechanism of tuning makes the fuzzy logic-based power system stabilizer adaptive to changes in the operating conditions. Therefore, variation in the system response, under a wide range of operating conditions, is less compared to the system response with a fixed-parameter conventional PSS. The performance of the AFPSS has been tested by simulation and experimental studies. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4603061&sortType%3Das [...]