Title :
Self-tuning of sensorless switched reluctance motor drives with online parameter identification
Author :
Islam, Mohammad S. ; Husain, Iqbal
Author_Institution :
Dept. of Electr. Eng., Akron Univ., OH, USA
Abstract :
The self-tuning capability of sensorless switched reluctance motor (SRM) drives is presented in this paper. A nonlinear machine model with online parameter identification is adapted with a sliding-mode observer (SMO) based sensorless technique. The parameter identification method makes position and speed estimation more accurate and robust towards any measurement noise and model uncertainty. Superior dynamic performance is achieved by updating machine parameters in real time. Online identification enables self-tuning of sensorless SRM drives without the need for a priori knowledge of the machine characteristics
Keywords :
adaptive control; control system analysis; control system synthesis; machine theory; machine vector control; observers; parameter estimation; position control; reluctance motor drives; self-adjusting systems; variable structure systems; velocity control; control simulation; dynamic performance; nonlinear machine model; online parameter identification; position estimation; robustness; self-tuning capability; sensorless control technique; sensorless switched reluctance motor drives; sliding-mode observer; speed estimation; Manufacturing; Noise measurement; Noise robustness; Packaging machines; Parameter estimation; Position measurement; Reluctance machines; Reluctance motors; Tuning; Velocity measurement;
Conference_Titel :
Industry Applications Conference, 2000. Conference Record of the 2000 IEEE
Conference_Location :
Rome
Print_ISBN :
0-7803-6401-5
DOI :
10.1109/IAS.2000.882115
