Model Predictive Voltage Control for Linear Induction Machine Without Weighting Factor
ID:8 View Protection:ATTENDEE Updated Time:2021-06-29 15:08:38 Hits:170 Oral Presentation

Start Time:2021-07-02 08:30 (Asia/Shanghai)

Duration:20min

Session:[S3] Concurrent Session 3 [S3-1] Oral Session 3 & 6

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Abstract
The conventional model predictive thrust control strategy for linear induction machines (LIMs) needs to determine proper weighting factors, and the tuning procedures are tedious by enumerating multiple try cases. In order to solve the aforementioned problems, a finite-set model predictive voltage control (FS-MPVC) is proposed in this work. This new method can eliminate the use of the weighting factor from the cost function and reduce calculation burden. Based on the deadbeat concept, the reference voltage vector is predicted, which can be used to construct a cost function. Whole comparison between the conventional finite set model predictive thrust control (FS-MPTC) and the proposed FS-MPVC has been made by comprehensive simulation and analysis. The results have demonstrated that, proposed FS-MPVC, can get quicker tracing speed and lower thrust ripples in response to those of the FS-MPTC.
Keywords
Model Predictive Voltage Control, Linear Machines, Weighting factor less
Speaker
Samir Hamad
Huazhong University of Science and Technology

- (31 December 2010 – 7 April 2016) Demonstrator, Department of process control Technology, Faculty of Technology and Education, Beni-Suef University, Beni-Suef, Egypt.
- (April 2016 - Currently) Assistant Lecturer, Department of process control Technology, Faculty of Technology and Education, Beni-Suef University, Beni-Suef, Egypt.
- Currently, working toward the Ph.D. degree with the State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan, China.
- Research interest is in the fields of power electronic converters, electrical machine control and predictive control.

Submission Author
Samir Hamad Huazhong University of Science and Technology
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