Speed Estimation Error of Sensorless Induction Motor Drives Using Soft Computing Technique

High-performance applications of sensor less systems require high accuracy of speed estimation over a wide speed range extending from very low and zero-speed operations to high speeds beyond the rating. Parallel speed and stator resistance identification schemes of sensor less induction motor drives have been introduced to overcome the problem of resistance variation Stator terminal voltages and currents are measured and filtered using analog circuitry Activation of the stator resistance adaptation mechanism quickly compensates the initial error in the estimated stator resistance value and therefore eliminates the initial speed estimation error. As a consequence, the actual and estimated speeds become in very good agreement. Low and zero-speed sensor less operation have also been investigated by the proposed SMO combined with the online stator resistance adaptation scheme.