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Optimization of delayed-state Kalman-filter-based algorithm via differential evolution for sensorless control of induction motors / Salvatore, Nadia in IEEE transactions on industrial electronics, Vol. 57 N° 1 (Janvier 2010) 

Public ISBD [article]  in IEEE transactions on industrial electronics > Vol. 57 N° 1 (Janvier 2010) . - pp. 385 - 394 Titre : Optimization of delayed-state Kalman-filter-based algorithm via differential evolution for sensorless control of induction motors Type de document : texte imprimé Auteurs : Salvatore, Nadia, Auteur ; Caponio, Andrea, Auteur ; Neri, Ferrante, Auteur Article en page(s) : pp. 385 - 394 Note générale : Génie électrique Langues : Anglais (eng) Mots-clés : AC  motor  drives  Algorithms  Covariance  matrices  Evolutionary  algorithms  (EAs)  Induction-motor  (IM)  drives  Kalman  filtering  Optimization  methods  Parameter  estimation  Speed  sensorless  State  estimation  Velocity  control Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : This paper proposes the employment of the differential evolution (DE) to offline optimize the covariance matrices of a new reduced delayed-state Kalman-filter (DSKF)-based algorithm which estimates the stator-flux linkage components, in the stationary reference frame, to realize sensorless control of induction motors (IMs). The DSKF-based algorithm uses the derivatives of the stator-flux components as mathematical model and the stator-voltage equations as observation model so that only a vector of four variables has to be offline optimized. Numerical results, carried out using a low-speed training test, show that the proposed DE-based approach is very promising and clearly outperforms a classical local search and three popular metaheuristics in terms of quality of the final solution for the problem considered in this paper. A novel simple stator-flux-oriented sliding mode (SFO-SM) control scheme is online used in conjunction with the optimized DSKF-based algorithm to improve the robustness of the sensorless IM drive at low speed. The SFO-SM control scheme has closed loops of torque and stator-flux linkage without proportional-plus-integral controllers so that a minimum number of gains has to be tuned. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5280262 [article] Optimization of delayed-state Kalman-filter-based algorithm via differential evolution for sensorless control of induction motors [texte imprimé] / Salvatore, Nadia, Auteur ; Caponio, Andrea, Auteur ; Neri, Ferrante, Auteur . - pp. 385 - 394. Génie électrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 57 N° 1 (Janvier 2010) . - pp. 385 - 394 Mots-clés : AC  motor  drives  Algorithms  Covariance  matrices  Evolutionary  algorithms  (EAs)  Induction-motor  (IM)  drives  Kalman  filtering  Optimization  methods  Parameter  estimation  Speed  sensorless  State  estimation  Velocity  control Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : This paper proposes the employment of the differential evolution (DE) to offline optimize the covariance matrices of a new reduced delayed-state Kalman-filter (DSKF)-based algorithm which estimates the stator-flux linkage components, in the stationary reference frame, to realize sensorless control of induction motors (IMs). The DSKF-based algorithm uses the derivatives of the stator-flux components as mathematical model and the stator-voltage equations as observation model so that only a vector of four variables has to be offline optimized. Numerical results, carried out using a low-speed training test, show that the proposed DE-based approach is very promising and clearly outperforms a classical local search and three popular metaheuristics in terms of quality of the final solution for the problem considered in this paper. A novel simple stator-flux-oriented sliding mode (SFO-SM) control scheme is online used in conjunction with the optimized DSKF-based algorithm to improve the robustness of the sensorless IM drive at low speed. The SFO-SM control scheme has closed loops of torque and stator-flux linkage without proportional-plus-integral controllers so that a minimum number of gains has to be tuned. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5280262