Torque-ripple minimization in switched reluctance motors using adaptive fuzzy control

An adaptive fuzzy control scheme for the torque-ripple minimization of switched reluctance machines is presented. The fuzzy parameters are initially chosen randomly and then adjusted to optimize the control. The controller produces smooth torque up to the motor base speed. The torque is generated ov...

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Bibliographic Details
Published in:IEEE transactions on industry applications 1999-03, Vol.35 (2), p.461-468
Main Authors: Mir, S., Elbuluk, M.E., Husain, I.
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive control systems
Commutation
Density
Error correction
Fuzzy control
Inductance
Minimization
Motors
Optimization
Programmable control
Reluctance
Reluctance machines
Reluctance motors
Rotors
Torque
Torque control
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Summary:An adaptive fuzzy control scheme for the torque-ripple minimization of switched reluctance machines is presented. The fuzzy parameters are initially chosen randomly and then adjusted to optimize the control. The controller produces smooth torque up to the motor base speed. The torque is generated over the maximum positive torque-producing region of a phase. This increases the torque density and avoids high current peaks. The controller is robust toward errors in the rotor position information, which means inexpensive crude position sensors can be used. Detailed simulation and experimental results are presented. The controller shows good response in both cases.
ISSN:0093-9994
1939-9367
DOI:10.1109/28.753642