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

Abstract

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.