Optimizing an extended luenberger speed observer for single-phase induction motor drives based on genetic algorithms

This research proposes algorithm development of a speed observer for single-phase induction motor drives. Although, many estimation schemes that have been commonly used for three-phase induction motors exist, a full-order extended Luenberger stat observer was adapted for used with single-phase induction motors in this paper. Due to asymmetrical stator windings, mathematical modeling used for estimation was needed to be developed and therefore was a rigid foundation in order to implement a high performance drive for single-phase induction motors, for example, a sensorless scheme incorporating with vector control or field oriented control. In addition, genetic algorithms, one of powerful intelligent search techniques, was employed in order to optimize a set of parameters required by the developed extended Luenberger speed observer. To verify accuracy of the proposed algorithm, a 0.37-kW, 220 V, 50 Hz single-phase induction motor was used for test. As a result, the effectiveness of the proposed optimized extended Luenberger speed observer was confirmed.