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Imposed Weighting Factor Optimization Method for Torque Ripple Reduction of IM Fed by Indirect Matrix Converter with Predictive Control Algorithm
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  • Imposed Weighting Factor Optimization Method for Torque Ripple Reduction of IM Fed by Indirect Matrix Converter with Predictive Control Algorithm
  • Imposed Weighting Factor Optimization Method for Torque Ripple Reduction of IM Fed by Indirect Matrix Converter with Predictive Control Algorithm
저자명
Uddin. Muslem,Mekhilef. Saad,Rivera. Marco,Rodriguez. Jose
간행물명
Journal of electrical engineering & technology
권/호정보
2015년|10권 1호|pp.227-242 (16 pages)
발행정보
대한전기학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.