Intelligent control of induction motor without speed sensor

Mohamed Elgohary, E. Gouda, S. S. Eskander


This paper presents a proposed sensorless algorithm for Induction Motor (IM) speed control based on Artificial Neural Networks (ANNs). The ANN applied to estimate the motor speed and using the motor voltages, currents, and the reference speed. The Indirect Rotor Field Oriented (IRFO) technique is applied to control the motor. It has advantages of insensitivity to stator resistance variation and it doesn’t required measurement of the rotor flux. It is designed based on the Proportional Integral (PI) controller. The Particle Swarm Optimization (PSO) algorithm is used as a good solution for the problems associated with the design of the PI gains. The PSO is compared with the conventional methods. The comparative results show the PSO-PI controller is better than the conventional one. The proposed controller (PSO-PI) is then integrated with the ANN speed estimator. The MATLAB/Simulink is used for the simulation of the system. The obtained simulation results for the estimated speeds based on the proposed technique are very close to the actual ones.



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