Journal of Applied Science and Engineering

Published by Tamkang University Press

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1.60

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A. Babazadeh1 and H. R. Karimi This email address is being protected from spambots. You need JavaScript enabled to view it.2

1Institute of Electrical Drives, Power Electronics and Devices, University of Bremen, Bremen, Germany
2Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran


 

Received: April 25, 2005
Accepted: September 30, 2005
Publication Date: June 1, 2006

Download Citation: ||https://doi.org/10.6180/jase.2006.9.2.05  


ABSTRACT


This paper deals with adaptive output tracking of a transverse flux permanent magnet machine as a nonlinear system with unknown nonlinearities by utilizing Takagi-Sugeno type neuro-fuzzy networks. The technique of feedback linearization and H control are used to design an adaptive control law for compensating the unknown nonlinear parts, such the effect of cogging torque, as a disturbance on the rotor angle and angular velocity tracking performances. Finally, the capability of the proposed method is shown by the simulation results.


Keywords: Neuro-fuzzy, Output Tracking, Transverse Flux Permanent Magnet Machines


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