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Impact of Observability and Multi-objective Optimization on the Performance of Extended Kalman Filter for DTC of AC Machines
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Publication Year
2019-01-30
Publisher
Korean Institute of Electrical Engineers
Citation
Journal of Electrical Engineering and Technology, Vol.14, pp.231-242
Keyword
DTCExtended Kalman filterInduction motorInstructionsMulti-objective optimizationNSGA II
Mesh Keyword
Constant switching frequencyDirect torque controlFitness functionsInstructionsNon-dominated sorting genetic algorithm - iiNSGA-IISpeed variationsVery low frequency
All Science Classification Codes (ASJC)
Electrical and Electronic Engineering
Abstract
It is well known that the selection of extended Kalman filter (EKF) covariance elements has a considerable bearing on the effectiveness of EKF performance. The observability at very low frequency is also an essential property for the selection of EKF elements. This paper investigates the optimization of the EKF covariance elements when zero frequency is included in the training profile for direct torque control (DTC) of induction motor. In addition, the paper studies the optimization of EKF by speed and torque fitness functions using a non-dominated sorting genetic algorithm-II at zero and high speeds under stable flux regulation. For this purpose, DTC with constant switching frequency controller which has the capability of establishing continuous flux rotation regardless of speed variation is used. The optimized results of EKF for both DTC motor drives and speed and torque cost functions are verified experimentally.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/30776
DOI
https://doi.org/10.1007/s42835-018-00019-3
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Type
Article
Funding
Acknowledgements This research was supported by a Grant (no. 20172020108970) from the Korea Institute of Energy Technology Evaluation and Planning (KETEP) that was funded by the Ministry of Trade, Industry and Energy (MOTIE).
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Lee, Kyo-Beum이교범
Department of Electrical and Computer Engineering
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