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Title: Experimental verification of adaptive and robust trajectory tracking controllers for switched reluctance motors

Book ·
OSTI ID:70843
 [1]; ;  [2]
  1. Clarkson Univ., Potsdam, NY (United States)
  2. Clemson Univ., SC (United States)

Integrator backstepping design techniques have recently been used to develop voltage level control algorithms for various classes of electric machines. The resulting control algorithms yield rigorous stability results that are attractive for motor drive applications for several reasons: (1) they can compensate for typically neglected electrical dynamics associated with the motor drive system, (2) they can compensate for a variety of uncertainties throughout the entire drive system (i.e., both modeled and unmodelled electromechanical dynamics), and (3) they can be designed to operate with only partial state measurements (i.e., sensorless control). Despite this promising outlook, few backstepping based algorithms have been experimentally verified, primarily due to their recent theoretical emergence. This paper examines two backstepping based algorithms for switched reluctance (SR) machines which use full-state measurements (i.e., motor position, velocity, and per phase winding currents), to yield rigorous theoretical stability results on the rotor trajectory tracking error despite uncertainty in the SR motor drive system. The controllers incorporate a smooth commutation strategy for the shared specification of the individual SR phase currents. The proposed controllers are experimentally verified using a digital signal processor based data acquisition and control system, and the performance results compared to a backstepping based, exact model knowledge control algorithm.

OSTI ID:
70843
Report Number(s):
CONF-941216-; TRN: 95:004350-0030
Resource Relation:
Conference: 33. Institute of Electrical and Electronic Engineers (IEEE) conference on decision and control, Orlando, FL (United States), 14-16 Dec 1994; Other Information: PBD: 1994; Related Information: Is Part Of Proceedings of the 33rd IEEE conference on decision and control; PB: 4347 p.
Country of Publication:
United States
Language:
English

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