DocumentCode
3086595
Title
Brushless DC generator controlled by predictive algorithm
Author
Gatto, G. ; Marongiu, I. ; Perfetto, A. ; Serpi, A.
Author_Institution
Dipt. di Ing. Elettr. ed Elettron., Univ. di Cagliari, Cagliari, Italy
fYear
2009
fDate
9-11 June 2009
Firstpage
727
Lastpage
732
Abstract
A predictive control of a brushless DC generator is presented in this paper. Starting from the reference value of the electromagnetic torque developed by the generator, in order to satisfy the requirement of the tracking characteristic of the prime-mover, the switching pattern of the AC/DC converter is determined at each sampling period. The inverter commands are determined on the basis of constraints of minimum Joule losses and minimum torque ripple. A simulation study of a conversion system supplying a constant voltage DC grid is carried out in Matlab-Simulink environment. The simulation results of the system controlled by the proposed algorithm are compared to those of the same system achieved by traditional control. The comparison highlights the better performance of the generator by using the proposed control technique instead of the traditional one.
Keywords
AC-DC power convertors; DC generators; brushless machines; invertors; machine control; power grids; predictive control; switching convertors; AC-DC converter; Joule loss; Matlab-Simulink environment; brushless DC generator control; constant voltage DC grid; converter switching pattern; electromagnetic torque; inverter; predictive control; prime-mover tracking characteristics; torque ripple; AC generators; Character generation; DC generators; DC-DC power converters; Inverters; Prediction algorithms; Predictive control; Sampling methods; Torque; Voltage; Brushless Machines; Permanent Magnet Generators; Predictive Control; Torque Control;
fLanguage
English
Publisher
ieee
Conference_Titel
Clean Electrical Power, 2009 International Conference on
Conference_Location
Capri
Print_ISBN
978-1-4244-2543-3
Electronic_ISBN
978-1-4244-2544-0
Type
conf
DOI
10.1109/ICCEP.2009.5211973
Filename
5211973
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