Intelligent neuro controller based speed and torque control of five phase switched reluctance motor

Abstract

The electric drives play an important role on the productivity to any industry. Recently the progress made in the motor design and power electronic control technology has promoted the capability of Switched Reluctance Motor (SRMs) in high performance industry application. This is made possible by the excellent electromagnetic operation of an SRM which is achieved by the proper excitation and control. A SRM has several desirable features like simple construction, high reliability and low cost. Its operation at high speeds made it suitable for the high temperature and hazardous environment applications. SRM are relatively simple electric machines but are difficult to model and control. It has its own drawbacks like large torque ripple, highly nonuniform torque and large noise. Due to the above reasons the design of the control system is more complex. For overcoming the above drawback Direct Torque Control (DTC) is introduced with SRM for improving its efficiency, compared to other conventional control techniques. DTC is simple algorithm to reduce the torque ripples. This reduction in torque ripples and speed control for industrial drive applications needs an effective controller. Hence a neuro based DTC is proposed and implemented with 5-phase 10/8 SRM. This intelligent controller can make the SRM drives to be used for the applications which require the features as robustness, wide speed range, efficiency or high dynamics. Here, simulation of the neuro based DTC for SRM is performed by using MATLAB/simulink and the results are validated according to the theoretical analysis.