Improving Quality of Movement in a Linear Switched Reluctance Motor Using a Fuzzy Logic System

This work deals with minimizing fluctuations of propulsion force and improving the motion quality in a linear switched reluctance motor. In order to minimize the jerks in the moving part of the motor, a new profile has been used to generate an appropriate reference speed profile. The results indicate that at speed 0.5 m/s, the motor reaches its command speed at the proposed time while, using conventional speed profile it takes almost 1.4 times the desired time. In order to control the speed and incease the motion quality, a simple fuzzy logic system has been used which is able to overcome the uncertainties problem in nonlinear systems. The fuzzy control system can regulate the motor performance so that it tracks the reference speed with minimum error and fluctuation. To illustrate the performance of the fuzzy method, a conventional PI method along with a model reference adaptive control (MRAC) strategy have been applied to the motor and the obtained results for three control methods have been compared. Speed overshoot using conventional PI method is about 20 percent of the final speed while this is about 6 percent for fuzzy and MRAC methods. The system is designed and its efficiency is shown through simulation and experimental tests in different performance situations . The obtained results confirm that the fuzzy strategy outperforms other methods.