APA 6th Edition Chekkouri, M.R., Català i López, J., Aldabas Rubira, E. i Romeral Martínez, L. (2003). Fuzzy Adaptive Control of an Induction Motor Drive. Automatika, 44. (3-4), 113-122. Preuzeto s https://hrcak.srce.hr/6770
MLA 8th Edition Chekkouri, Mohamed Rachid, et al. "Fuzzy Adaptive Control of an Induction Motor Drive." Automatika, vol. 44., br. 3-4, 2003, str. 113-122. https://hrcak.srce.hr/6770. Citirano 21.10.2021.
Chicago 17th Edition Chekkouri, Mohamed Rachid, Jordi Català i López, Emiliano Aldabas Rubira i Luis Romeral Martínez. "Fuzzy Adaptive Control of an Induction Motor Drive." Automatika 44., br. 3-4 (2003): 113-122. https://hrcak.srce.hr/6770
Harvard Chekkouri, M.R., et al. (2003). 'Fuzzy Adaptive Control of an Induction Motor Drive', Automatika, 44.(3-4), str. 113-122. Preuzeto s: https://hrcak.srce.hr/6770 (Datum pristupa: 21.10.2021.)
Vancouver Chekkouri MR, Català i López J, Aldabas Rubira E, Romeral Martínez L. Fuzzy Adaptive Control of an Induction Motor Drive. Automatika [Internet]. 2003 [pristupljeno 21.10.2021.];44.(3-4):113-122. Dostupno na: https://hrcak.srce.hr/6770
IEEE M.R. Chekkouri, J. Català i López, E. Aldabas Rubira i L. Romeral Martínez, "Fuzzy Adaptive Control of an Induction Motor Drive", Automatika, vol.44., br. 3-4, str. 113-122, 2003. [Online]. Dostupno na: https://hrcak.srce.hr/6770. [Citirano: 21.10.2021.]
Sažetak Industrial applications increasingly require electric drives with good position command tracking and load regulation responses. These conditions can only be achieved by adaptive-type control because of the loading conditions, inertias and system parameters all change during the motion. For this paper an Adaptive Speed Controller for AC drives with a very low computational algorithm was developed. The authors propose self-tuning control based on a supervisory fuzzy adaptation. The supervisor continuously monitors the status of the system and changes the Ki parameter of a standard PDF controller to adapt it to the plant’s evolution. The fuzzy logic adaptive strategy was readily implemented and showed very fast learning features and very good tracking and regulation characteristics. The stability of the controller developed was also analysed, and experimental results demonstrated the robustness of the suggested algorithm in contending with varying load and torque disturbance.