Self-tuning adaptive neurocontroller for brushless DC motors

This paper describes a self-tuning adaptive neurocontroller for brushless DC motors. Nonlinear and unknown motor dynamics are identified by using a multilayer neural network and the control input for the motor is derived from the identified model. The effect of the load torque on the control system...

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Bibliographic Details
Published in:International journal of electronics 2001-01, Vol.88 (1), p.103-114
Main Authors: Albostan, Ayhan, Gökbulut, Muammer
Format: Article
Language:English
Subjects:
Applied sciences
Electric, optical and optoelectronic circuits
Electrical engineering. Electrical power engineering
Electronics
Exact sciences and technology
Neural networks
Power electronics, power supplies
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Summary:This paper describes a self-tuning adaptive neurocontroller for brushless DC motors. Nonlinear and unknown motor dynamics are identified by using a multilayer neural network and the control input for the motor is derived from the identified model. The effect of the load torque on the control system is damped by filtering the control input. Simulation and experimental results show that the self-tuning adaptive neurocontrol has a good tracking performance but needs an adaptive filter and a parallel PI controller in the case of disturbances.
ISSN:0020-7217
1362-3060
DOI:10.1080/00207210150198329