الفهرس 
Introduction to Switched reluctance motorOnly 14 pages are availabe for public view
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Abstract
Due to the advances on sensors, power electronics and signal processing, switched reluctance motor
has gained a lot of commercial and academic interest.
Switched Reluctance Motor (SRM) construction simplicity makes it inexpensive, in addition to its
reliability, high speed capability, cooling, ruggedness and high torque to inertia ratio makes it a
superior choice in different applications. However, acoustic noise and excessive torque ripple,
especially at low speeds prevented SRM from widespread use.
Actually there are two approaches to reduce torque ripples; one of them is to improve the magnetic
design of the motor, while the other is to use sophisticated electronic control.
This thesis combines these two approaches to reduce torque ripples of switched reluctance motor
through building two multi-layered switched reluctance motor (MSRM), the first one is Doublelayer
switched reluctance motor (DLSRM) controlled by a hybrid intelligent system known as
adaptive neuro-fuzzy inference system . And also building triple layer switched reluctance motor
(TLSRM) controlled by fuzzy logic controller.
Both models of DLSRM and TLSRM was built using MATLAB /SIMULINK. For comparison we
also build a model of SRM of the same size as DLSRM, so according to these models, different
controller were used to control DLSRM ,TLSRM and SRM the first one is proportional integral
controller and the second intelligent controller adaptive neuro-fuzzy inference system Then fuzzy
logic controller.
The simulation results of DLSRM compared with single layer switched reluctance motor for both
PI, FLC and ANFIS controllers show improvement in behavior of DLSRM controlled by ANFIS
through reduction in speed settling time as well as torque ripples.