DocumentCode
612804
Title
Predictive Direct Torque and Flux Control of an induction motor drive fed by a Direct Matrix Converter with reactive power minimization
Author
Zakaria, L. ; Barra, K.
Author_Institution
Dept. of Electr. Eng., Larbi Ben M´hidi Univ., Oum El Bouaghi, Algeria
fYear
2013
fDate
10-12 April 2013
Firstpage
34
Lastpage
39
Abstract
The paper presents a Predictive Direct Torque and Flux Control (PDTFC) of an induction machine fed by a Direct Matrix Converter (DMC). The method combines the merits of Finite States Model Predictive Control (FSMPC) with the ones of DTC control. The proposed control algorithm selects the switching state of the DMC that minimizes the error between torque and flux predictions to their computed values for all different voltage vectors. The optimal voltage vector that minimizes a cost function is then applied to the terminal of the induction machine. Moreover, the proposed predictive control is easily extended to minimize the reactive power in the voltage source side. The control method uses only one sample time and it is very intuitive since it is simple, multi-objective and provides best performances compared to other control laws (fast dynamic response, simple implementation).
Keywords
cost reduction; induction motor drives; machine control; matrix convertors; minimisation; predictive control; reactive power; torque control; DMC; DTC control; FSMPC; PDTFC; cost function minimization; direct matrix converter; error minimization; finite states model predictive control; induction machine; induction motor drive; predictive direct torque and flux control; reactive power minimization; voltage source; voltage vectors; Indexes; Integrated circuits; Inverters; Predictive models; Switches; Vectors; Induction motor; cost function; direct matrix converter; finite states-space model; predictive control; reactive power;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on
Conference_Location
Evry
Print_ISBN
978-1-4673-5198-0
Electronic_ISBN
978-1-4673-5199-7
Type
conf
DOI
10.1109/ICNSC.2013.6548707
Filename
6548707
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