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Makale detayı · 2017

The Comparisons of Optimized Extended Kalman Filters for Speed-Sensorless Control of Induction Motors

YÖKSİS OpenAlex SJR Q1 JCR Q1 Atıf 180 Üst %1 Yüzdelik 99.5% FWCI 20.53
Yıl
2017
Tür
article

Veri kaynağı ayrımı

  • YÖKSİS YÖKSİS makale kaydı
  • YÖKSİS dergi adı IEEE Transactions on Industrial Electronics
  • Katalog eşleşmesi (ISSN) IEEE Transactions on Industrial Electronics
  • OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)

Özet

OpenAlex · İngilizce

This paper presents the comparisons of optimized extended Kalman filters (EKFs) using different fitness functions for speed-sensorless vector control of induction motors (IMs). In order to achieve high performance estimations of states/parameter by EKF algorithm, state and noise covariance matrices must be accurately selected. For this aim, instead of using time-consuming trial-and-error method to determine those covariance matrices, in this paper EKF algorithm is optimized by differential evolution algorithm (DEA) and multi-objective DEA (MODEA) with the utilization of different fitness functions. The optimally obtained set of each covariance matrices is used in EKF algorithm built on the same IM model and thus, the estimation results of the optimized EKF algorithms are compared in real-time experiments in order to conclude which fitness function is better for motion control applications.

Konular

Atıflar

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180 atıf

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Yazarlar

  1. EMRAH ZERDALİ
  2. MURAT BARUT NİĞDE ÖMER HALİSDEMİR ÜNİVERSİTESİ