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The operation of a brushless permanent-magnet machine requires rotor-position information, which is used to control the frequency and phase angle of the machine's winding currents. Sensorless techniques for estimating rotor position from measurements of voltage and current have been the subject of intensive research. This paper reviews the state of the art in these sensorless techniques, which are broadly classified into three types: motional electromotive force, inductance, and flux linkage. Index Terms--Brushless machines, estimation, permanent-magnet (PM) machines, position measurement, reviews.

This paper describes a new algorithm for the estimation of rotor position in a switched reluctance motor. It is based on a recursive least-squares estimator deducing both position and speed. A particular advantage of the algorithm is its ability to extract information about rotor position at very low speeds (one electrical cycle per minute) from voltage and current waveforms sampled only at the converter switching frequency. Experimental results for a 12/8 motor demonstrate that estimation is possible over the full range of operating conditions, including the field-weakening region, with a typical accuracy of better than two mechanical degrees. The paper also illustrates the performance of the algorithm by showing it operating within a sensorless position controller. Index Terms--Estimation, least-squares methods, position measurement, reluctance motor drives.

Tuning of electric drive speed controllers is complicated by nonlinearities. Usual practice obtains controller settings with conventional linear analysis methods and then tunes the settings using trial-and-error methods during commissioning. An alternative approach, using genetic algorithms for the online tuning, is proved experimentally to optimize the drive's response efficiently. These settings are critically dependent on operating point. Index Terms--Electric drives, genetic algorithms, speed control, tuning.