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On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural NetworksA real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.
Document ID
Document Type
Conference Paper
Rubaai, Ahmed
(Howard Univ. Washington, DC United States)
Date Acquired
August 17, 2013
Publication Date
July 1, 1996
Publication Information
Publication: HBCU's Research Conference Agenda and Abstracts
Subject Category
Electronics And Electrical Engineering
Report/Patent Number
Accession Number
Distribution Limits
Work of the US Gov. Public Use Permitted.

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