Fast Controling Induction Motor Speed Estimation Using Neuro-Fuzzy

Speed control performance of induction motors are affected by parameter variations and non linearity in the induction motor. This paper introduces a novel adaptive speed control of induction motor drives using Neuro-Fuzzy. Speed estimation method for control of induction machine drive has gained increasing interest among the research communities. The supremacy of an induction machine drive depends on the speed estimation accuracy. To ensure accurate speed estimation over a wide range, from zero to high levels exceeding the rated speed, accurate values of the machine’s parameters, the aim of the simulation proposed control is to improve the performance and robustness of the induction motor drives under non linear loads and parameter variations. Both the design of the fuzzy controller and its integration with neural network in a global control system are discussed. Simulation results shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the usefulness of the neuro-fuzzy controller in high performance drives with uncertainly