ANFIS Based Speed Controller for a Direct Torque Controlled Induction Motor Drive

Abstract

This paper presents a Neuro-Fuzzy adaptive controller for speed control of a three phase direct torque controlled induction motor drive. The Direct Torque Control (DTC) scheme is one of the most advanced methods for controlling the flux and electromagnetic torque of machines. Control of electromagnetic torque/speed in these drives for high performance applications requires a highly robust and adaptive controller. Adaptive Neural-Fuzzy Inference System (ANFIS) is a hybrid between Artificial Neural Networks (ANN) and Fuzzy Logic Control (FLC) that enhances the execution of direct torque controlled drives and overcomes the difficulties in the physical implementation of high performance drives. MATLAB/SIMULINK implementation of 15 hp, 50 Hz, 4 pole squirrel cage induction motor controlled with the DTC scheme is presented in this paper. The PI controller used for speed control in conventional DTC drives is substituted by the ANFIS based controller. Simulation results show the use of ANFIS decreases the response time along with reduction in torque ripples.