08-10-2010, 03:44 PM
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FUZZY LOGIC CONTROL OF A SWITCHED RELUCTANCE MOTOR
Abstract
This paper presents the use of fuzzy logic control (FLC) for switched reluctance motor (SRM) speed. The FLC performs a PI-like control strategy, giving the current reference variation
based on speed error and its change. The performance of the drive system was evaluated through digital simulations through the toolbox Simulink of Matlab program.
INTRODUCTION
The switched reluctance motor (SRM) has becoming an attractive alternative in variable speed drives, due to its advantages such as structural simplicity, high reliability and low cost . Many papers have been written about SRM concerning design and control . An important characteristic of the SRM is that the inductance of the magnetic circuit is a nonlinear function of the phase current and rotor position. So, for the control and optimization of this drive, a precise magnetic model is necessary. To obtain this model is not an easy task, because the magnetic circuit operates at varying levels of saturation
under operating conditions . Further, the nonlinear characteristic of this plant represents a challenge to classical control. To overcome this drawback, some alternatives have been suggested, using fuzzy and neuronal systems.
This paper proposes to control SR drives using fuzzy logic control (FLC), which is mainly applied to complex plants, where it is difficult to obtain accurate mathematical model or when the
model is severely nonlinear. FLC has the ability to handle numeric and linguistic knowledge simultaneously.
In this paper we present a study by simulation of the use of a FLC for SR drive. The SRM simulated has a strusture of six poles on the stator and four on the rotor and power of 1 HP . The nonlinear model of this motor was simulated with the Matlab Simulink package and two tables were used to represent the nonlinearities: I(θ,λ), current in function of rotor position and flux, and τ(θ,I) , torque in function of rotor position and current. The objective of the FLC is to present a good performance, even if the two tables for a given motor were not accurately determined.
The proposed control can be divided in two parts. The first employs FLC and will generate current reference variations, based on speed error and its change. The second one has the function of selecting the phase that should be fed to optimize the torque, based on rotor position.
