الفهرس | Only 14 pages are availabe for public view |
Abstract This work aims at utilizing the artificial intelligence methods for torque control of switched reluctance machine in motor mode. The main challenge of switched reluctance motor control is the dependence on two switching angles and current amplitude. These quantities allow the control of phase current during excitation. The current decay period is uncontrolled.This thesis proposes the correlative-angles switching technique to facilitate the control of phase current during the entire conduction period. The technique is integrated with the classical and intelligent control strategies to investigate its reliability, capability as well as operation limits. The resulting control schemes combine current control for low speed operation and switching angles control for high speed operation. The overall control system have been designed and simulated for different operation conditions. The simulation study includes open and closed loop operation of switched reluctance drive system. The study covers the utilization of the drive system for traction application using motion pattern using either conventional proportional integral derivative (PID) controller or the intelligent fuzzy controller for both speed and torque control. To decrease torque ripple,torque control of switched reluctance motor using torque sharing function has been utilized. It has been shown that the proposed correlative-angles switching technique is more effective at high speeds while the current control is more effective at low speeds. It was found that the speed error and torque ripples have been reduced when using the correlative-angles switching technique. |