In this study, a robust speed control based on adaptive neuro-fuzzy inference technique is proposed for asynchronous motors driven by indirect field oriented vector algorithm. The speed control performance of asynchronous motors is significantly influenced by nonlinear elements and parameter changes in the motor drive. Adaptive neuro-fuzzy controller, PI type classical controller and fuzzy logic controller have been separately developed for the speed control of a sample asynchronous motor. Parameters of ANFIS were tuned by an on-line direct self-tuning technique get better performance, stability and accuracy in speed control process. The performance of adaptive neuro-fuzzy, PI type classical and fuzzy logic controller have been examined for different references and loading conditions in the Matlab/Simulink environment. Simulation studies have demonstrated that the superiority of the ANFIS type controller is a clear reality over the other control methods.

Keywords: Adaptive neuro-fuzzy inference system (ANFIS), Fuzzy logic control (FLC), Indirect field oriented vector (IFOC) of asynchronous motor, Proportional integral (PI)