Documents disponibles écrits par cet auteur

A grey system modeling approach for sliding-mode control of antilock braking system / Kayacan, Erdal in IEEE transactions on industrial electronics, Vol. 56 N° 8 (Août 2009) 

Public ISBD [article]  in IEEE transactions on industrial electronics > Vol. 56 N° 8 (Août 2009) . - pp. 3244 - 3252 Titre : A grey system modeling approach for sliding-mode control of antilock braking system Type de document : texte imprimé Auteurs : Kayacan, Erdal, Auteur ; Oniz, Yesim, Auteur ; Kaynak, Okyay, Auteur Article en page(s) : pp. 3244 - 3252 Note générale : Génie électrique Langues : Anglais (eng) Mots-clés : Antilock  braking  system  (ABS)  GM(1,1)  Grey  system  theory  Sliding-mode  control Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : In this paper, a grey sliding-mode controller is proposed to regulate the wheel slip, depending on the vehicle forward velocity. The proposed controller anticipates the upcoming values of wheel slip and takes the necessary action to keep the wheel slip at the desired value. The performance of the control algorithm as applied to a quarter vehicle is evaluated through simulations and experimental studies that include sudden changes in road conditions. It is observed that the proposed controller is capable of achieving faster convergence and better noise response than the conventional approaches. It is concluded that the use of grey system theory, which has certain prediction capabilities, can be a viable alternative approach when the conventional control methods cannot meet the desired performance specifications. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4957103 [article] A grey system modeling approach for sliding-mode control of antilock braking system [texte imprimé] / Kayacan, Erdal, Auteur ; Oniz, Yesim, Auteur ; Kaynak, Okyay, Auteur . - pp. 3244 - 3252. Génie électrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 56 N° 8 (Août 2009) . - pp. 3244 - 3252 Mots-clés : Antilock  braking  system  (ABS)  GM(1,1)  Grey  system  theory  Sliding-mode  control Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : In this paper, a grey sliding-mode controller is proposed to regulate the wheel slip, depending on the vehicle forward velocity. The proposed controller anticipates the upcoming values of wheel slip and takes the necessary action to keep the wheel slip at the desired value. The performance of the control algorithm as applied to a quarter vehicle is evaluated through simulations and experimental studies that include sudden changes in road conditions. It is observed that the proposed controller is capable of achieving faster convergence and better noise response than the conventional approaches. It is concluded that the use of grey system theory, which has certain prediction capabilities, can be a viable alternative approach when the conventional control methods cannot meet the desired performance specifications. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4957103

Sliding-mode control with soft computing: a survey / Yu, Xinghuo in IEEE transactions on industrial electronics, Vol. 56 N° 9 (Septembre 2009) 

Public ISBD [article]  in IEEE transactions on industrial electronics > Vol. 56 N° 9 (Septembre 2009) . - pp. 3275-3285 Titre : Sliding-mode control with soft computing: a survey Type de document : texte imprimé Auteurs : Yu, Xinghuo, Auteur ; Kaynak, Okyay, Auteur Article en page(s) : pp. 3275-3285 Note générale : Génie Electrique Langues : Anglais (eng) Mots-clés : Génie  électrique  Commande  de  glissement Index. décimale : 621 Ingénierie mécanique en général. Technologie nucléaire. Ingénierie électrique. Machinerie Résumé : Sliding-mode control (SMC) has been studied extensively for over 50 years and widely used in practical applications due to its simplicity and robustness against parameter variations and disturbances. Despite the extensive research activities carried out, the key technical problems associated with SMC remain as challenging research questions due to demands for new industrial applications and technological advances. In this respect, soft computing (SC) is a rather recent development in intelligent systems which has provided alternative means for adaptive learning and control to overcome the key SMC technical problems. Substantial efforts in integration of SMC with SC have been placed in recent years with various successes. In this paper, we provide the state of the art of recent developments in SMC systems with SC, examining key technical research issues and future perspectives. DEWEY : 621 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=5200775&arnumber=5164946 [...] [article] Sliding-mode control with soft computing: a survey [texte imprimé] / Yu, Xinghuo, Auteur ; Kaynak, Okyay, Auteur . - pp. 3275-3285. Génie Electrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 56 N° 9 (Septembre 2009) . - pp. 3275-3285 Mots-clés : Génie  électrique  Commande  de  glissement Index. décimale : 621 Ingénierie mécanique en général. Technologie nucléaire. Ingénierie électrique. Machinerie Résumé : Sliding-mode control (SMC) has been studied extensively for over 50 years and widely used in practical applications due to its simplicity and robustness against parameter variations and disturbances. Despite the extensive research activities carried out, the key technical problems associated with SMC remain as challenging research questions due to demands for new industrial applications and technological advances. In this respect, soft computing (SC) is a rather recent development in intelligent systems which has provided alternative means for adaptive learning and control to overcome the key SMC technical problems. Substantial efforts in integration of SMC with SC have been placed in recent years with various successes. In this paper, we provide the state of the art of recent developments in SMC systems with SC, examining key technical research issues and future perspectives. DEWEY : 621 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=5200775&arnumber=5164946 [...]

Type 2 fuzzy neural structure for identification and control of time-varying plants / Abiyev, Rahib Hidayat in IEEE transactions on industrial electronics, Vol. 57 N° 12 (Décembre 2010) 

Public ISBD [article]  in IEEE transactions on industrial electronics > Vol. 57 N° 12 (Décembre 2010) . - pp. 4147 - 4159 Titre : Type 2 fuzzy neural structure for identification and control of time-varying plants Type de document : texte imprimé Auteurs : Abiyev, Rahib Hidayat, Auteur ; Kaynak, Okyay, Auteur Année de publication : 2011 Article en page(s) : pp. 4147 - 4159 Note générale : Génie électrique Langues : Anglais (eng) Mots-clés : Control  Fuzzy  identification  Fuzzy  neural  networks  (FNNs)  Type  2  fuzzy  system Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : In industry, most dynamical plants are characterized by unpredictable and hard-to-formulate factors, uncertainty, and fuzziness of information, and as a result, deterministic models usually prove to be insufficient to adequately describe the process. In such situations, the use of fuzzy approaches becomes a viable alternative. However, the systems constructed on the base of type 1 fuzzy systems cannot directly handle the uncertainties associated with information or data in the knowledge base of the process. One possible way to alleviate the problem is to resort to the use of type 2 fuzzy systems. In this paper, the structure of a type 2 Takagi–Sugeno–Kang fuzzy neural system is presented, and its parameter update rule is derived based on fuzzy clustering and gradient learning algorithm. Its performance for identification and control of time-varying as well as some time-invariant plants is evaluated and compared with other approaches seen in the literature. It is seen that the proposed structure is a potential candidate for identification and control purposes of uncertain plants, with the uncertainties being handled adequately by type 2 fuzzy sets. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5416278 [article] Type 2 fuzzy neural structure for identification and control of time-varying plants [texte imprimé] / Abiyev, Rahib Hidayat, Auteur ; Kaynak, Okyay, Auteur . - 2011 . - pp. 4147 - 4159. Génie électrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 57 N° 12 (Décembre 2010) . - pp. 4147 - 4159 Mots-clés : Control  Fuzzy  identification  Fuzzy  neural  networks  (FNNs)  Type  2  fuzzy  system Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : In industry, most dynamical plants are characterized by unpredictable and hard-to-formulate factors, uncertainty, and fuzziness of information, and as a result, deterministic models usually prove to be insufficient to adequately describe the process. In such situations, the use of fuzzy approaches becomes a viable alternative. However, the systems constructed on the base of type 1 fuzzy systems cannot directly handle the uncertainties associated with information or data in the knowledge base of the process. One possible way to alleviate the problem is to resort to the use of type 2 fuzzy systems. In this paper, the structure of a type 2 Takagi–Sugeno–Kang fuzzy neural system is presented, and its parameter update rule is derived based on fuzzy clustering and gradient learning algorithm. Its performance for identification and control of time-varying as well as some time-invariant plants is evaluated and compared with other approaches seen in the literature. It is seen that the proposed structure is a potential candidate for identification and control purposes of uncertain plants, with the uncertainties being handled adequately by type 2 fuzzy sets. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5416278