18-06-2012, 12:36 PM
Model Reference Adaptive Control of Five-Phase
IPM Motors Based on Neural Network
Model Reference Adaptive Control.pdf (Size: 538.02 KB / Downloads: 34)
Abstract
This paper presents a novel model reference adaptive
control of five-phase interior-permanent-magnet (IPM) motor
drives. The primary controller is designed based on an artificial
neural network (ANN) to simulate the nonlinear characteristics
of the system without knowledge of accurate motor models or
parameters. The proposed motor drive decouples the torque and
flux components of five-phase IPM motors by applying multiplereference-
frame transformation.
INTRODUCTION
INTERIOR-PERMANENT-MAGNET (IPM) motors are
widely used in various applications due to many advantages
such as high power density, high efficiency, and low operating
noise. The overall cost keeps dropping as a result of advances in
permanent-magnet manufacturing and technology. Much more
attention has been paid to permanent-magnet motors due to the
improvement of power electronics devices and variable speed
motor control technique.
MATHEMATICAL MODEL OF FIVE-PHASE IPM MOTORS
Five-Phase IPM Motor Equations
In this section, the mathematical model of five-phase IPM
motors will be derived using the multiple-reference-frame
transformation similar to Park’s transformation in three-phase
motors.
The five-phase IPM motor system provides an additional
degree of freedom by applying the multiple-reference-frame
transformation in (1), shown at the bottom of the page, where θ
is the electrical rotor angle.
Five-phase quantities in the stator reference frame will be
transformed into two rotating frames: the d–q rotor reference
frame which is rotating at synchronous speed and the d3–q3
frame which is rotating at three times the synchronous speed.
These two reference frames are fully decoupled, and the fundamental
components of signals are reflected into the d–q frame
with the third-order harmonics reflected into the d3–q3 frame.