Adaptive Control of Brushless DC Motor Using Neural Network Identification and Pole Shifting Controller
Eliwa, A., Sabry, W., El-Wakeel, A., Abou-Zayed, U. (2011). Adaptive Control of Brushless DC Motor Using Neural Network Identification and Pole Shifting Controller. EKB Journal Management System, 11(ASAT Conference, 17-19 May 2005), 837-845. doi: 10.21608/asat.2011.27192
A. Eliwa; W. Sabry; A. El-Wakeel; U. Abou-Zayed. "Adaptive Control of Brushless DC Motor Using Neural Network Identification and Pole Shifting Controller". EKB Journal Management System, 11, ASAT Conference, 17-19 May 2005, 2011, 837-845. doi: 10.21608/asat.2011.27192
Eliwa, A., Sabry, W., El-Wakeel, A., Abou-Zayed, U. (2011). 'Adaptive Control of Brushless DC Motor Using Neural Network Identification and Pole Shifting Controller', EKB Journal Management System, 11(ASAT Conference, 17-19 May 2005), pp. 837-845. doi: 10.21608/asat.2011.27192
Eliwa, A., Sabry, W., El-Wakeel, A., Abou-Zayed, U. Adaptive Control of Brushless DC Motor Using Neural Network Identification and Pole Shifting Controller. EKB Journal Management System, 2011; 11(ASAT Conference, 17-19 May 2005): 837-845. doi: 10.21608/asat.2011.27192

Adaptive Control of Brushless DC Motor Using Neural Network Identification and Pole Shifting Controller

International Conference on Aerospace Sciences and Aviation Technology
Article 50, Volume 11, ASAT Conference, 17-19 May 2005, May 2011, Page 837-845  XML PDF (1.21 MB)
Document Type: Original Article
DOI: 10.21608/asat.2011.27192
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Authors
A. Eliwa; W. Sabry; A. El-Wakeel; U. Abou-Zayed
Egyptian Armed Forces.
Abstract
In this paper adaptive control of a brushless DC motor (BLDCM) using neural network identification and pole shifting (PS) controller is presented. Proper system identification is one of the important factors that gives a good controller performance. This means that when the model parameter estimates are good, the controller output is good, whereas if the model parameter estimates are bad then almost surely the computed control will be bad. Proper selection of the identified system model order is also investigated. A comparison study between fuzzy logic controller and the proposed controller is also investigated.
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