Research On Intelligence Control Technology And Its Application In Switched Reluctance Drives

This thesis makes some studies in intelligence control and its application in switched reluctance drives(SRD).This paper provides a non-linear model of switched reluctance motor(SRM). The phase current and torque are calculated based on this non-linear model. A model of SRM's inductance is given with artificial neural network. According to SRM's characteristic, torque-ripple of SRM is reduced by designing expected torque.Fuzzy controller with self-adaptive proportion is constructed through modifying normal fuzzy controller.By using artificial neural network's learn ability and recollection ability, proportion parameter is adjusted online.lt improves the normal fuzzy controller's performance.A single neural cell self-adaptive controller is studied. Furthermore, a direct digital control system of SRM based on this single neural cell self-adaptive controller is designed by using MCS-80C196KB microprocessor.