RBF Identifier Based Adaptive Sugeno Type FLC for Vector Controlled Asynchronous Motor
MetadataShow full item record
CitationSIT SAMI, ÖZÇALIK HASAN RIZA, KILIÇ ERDAL, DOGMUŞ OSMAN (2016). RBF Identifier Based Adaptive Sugeno Type FLC for Vector Controlled Asynchronous Motor. IOSR Journal of Engineering (IOSRJEN), 6(12), 73-80.
In this paper a simulation study of Adaptive Sugeno type Fuzzy Logic Control (FLC) for indirect field oriented controlled (IFOC) asynchronous motor drive system have been suggested. The structure of control scheme consists of neural network identifier and FLC. The Radial Basis Function (RBF) neural network parameters are online updated by using back-propagation method. The consequent parameters of FLC are tuned online by using the RBF identified model. Speed control of asynchronous motor performance parameters such as steady state error, rise time, overshoot, undershoot and settling time are obtained for the suggested controller and compared with the conventional PI controller. Simulation results are included to show the suitability, effectiveness and robustness of the adaptive Sugeno type FLC. Adaptive Sugeno type FLC using the Matlab / Simulink simulation software was compared with the results obtained from conventional PI type controller.