Each day that passes, the electrical drives operation conditions become more demanding. The use of switched reluctance motors (SRM) has magnified sufficiently with the intelligent control strategies improvement for torque ripple minimization. Another important subject is the sensors' elimination, allowing the equipment price to be reduced. In this work, two new on-line learning control schemes to minimize the torque ripple in SRMs are proposed. The first scheme uses a sensor torque to measure the motor ripple. In the second one, the ripple compensation is designed without sensor neither a torque observer. It uses the error speed signal as an indirect ripple measure. The two algorithms are explained and simulation results are shown to describe and discuss their performance
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