Power system stabilizer design using an online adaptive neurofuzzy controller with adaptive input link weights / Ramirez-Gonzalez, M. in IEEE transactions on energy conversion, Vol. 23 n°3 (Septembre 2008)  

Public ISBD [article]  inIEEE transactions on energy conversion > Vol. 23 n°3 (Septembre 2008) . - pp. 914 - 922 Titre : Power system stabilizer design using an online adaptive neurofuzzy controller with adaptive input link weights Type de document : texte imprimé Auteurs : Ramirez-Gonzalez, M., Auteur ; Malik, O. P., Auteur Année de publication : 2008 Article en page(s) : pp. 914 - 922 Note générale : Energy conversion Langues : Anglais (eng) Mots-clés : Adaptive control  fuzzy set theory  gradient methods  neurocontrollers  power system stability Résumé : A neurofuzzy controller (NFC) with adaptive input link weights (ILWs) and working as an adaptive power system stabilizer is presented. The control structure of the proposed adaptive neurofuzzy power system stabilizers (ANFPSSs) consists of a neuroidentifier to track the dynamic behavior of the plant and an NFC to damp the low-frequency power system oscillations. Usually, the input membership functions (IMFs) and consequent parameters (CPs) are adapted in order to enhance the performance of the NFC. However, the adjustment of IMFs can be realized indirectly by the tuning of ILWs introduced here, which is simpler due to the small number of parameters involved. Therefore, in this paper, ILWs and CPs are updated online by the gradient descent method. Simulation studies over a range of operating conditions and disturbances in a single machine-infinite bus system and a multimachine power system demonstrate the improvement in the dynamic performance of the system with the proposed ANFPSS. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4537513&sortType%3Das [...] [article] Power system stabilizer design using an online adaptive neurofuzzy controller with adaptive input link weights [texte imprimé] / Ramirez-Gonzalez, M., Auteur ; Malik, O. P., Auteur . - 2008 . - pp. 914 - 922. Energy conversion Langues : Anglais (eng) in IEEE transactions on energy conversion > Vol. 23 n°3 (Septembre 2008) . - pp. 914 - 922 Mots-clés : Adaptive control  fuzzy set theory  gradient methods  neurocontrollers  power system stability Résumé : A neurofuzzy controller (NFC) with adaptive input link weights (ILWs) and working as an adaptive power system stabilizer is presented. The control structure of the proposed adaptive neurofuzzy power system stabilizers (ANFPSSs) consists of a neuroidentifier to track the dynamic behavior of the plant and an NFC to damp the low-frequency power system oscillations. Usually, the input membership functions (IMFs) and consequent parameters (CPs) are adapted in order to enhance the performance of the NFC. However, the adjustment of IMFs can be realized indirectly by the tuning of ILWs introduced here, which is simpler due to the small number of parameters involved. Therefore, in this paper, ILWs and CPs are updated online by the gradient descent method. Simulation studies over a range of operating conditions and disturbances in a single machine-infinite bus system and a multimachine power system demonstrate the improvement in the dynamic performance of the system with the proposed ANFPSS. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4537513&sortType%3Das [...]

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