Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor drive

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Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor drive

Yahia Laamari - Nama Orang; Kheireddine Chafaa - Nama Orang; Belkacem Athamena - Nama Orang;

A novel method based on a combination of the extended Kalman filter with particle swarm optimization (PSO) to estimate the speed and rotor flux of an induction motor drive is presented. The proposed method will be performed in two steps. As a first step, the covariance matrices of state noise and measurement noise will be optimized in an off-line manner by the PSO algorithm. As a second step, the optimal values of the above covariance matrices are injected in our speed–rotor flux estimation loop (on-line). Computer simulations of the speed and rotor flux estimation have been performed to investigate the effectiveness of the proposed method. Simulations and comparison with genetic algorithms show that the results are very encouraging and achieve good performances.

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Judul Seri: ELECTRICAL ENGINEERING
No. Panggil: -
Penerbit: Berlin : Springer-Verlag Berlin Heidelberg., 2015
Deskripsi Fisik: Electr Eng (2015) 97:129–138
Bahasa: English
ISBN/ISSN: DOI 10.1007/s00202-0
Klasifikasi: -
Tipe Isi: -
Tipe Media: -
Tipe Pembawa: -
Edisi: (2015) 97:129–138
Subjek: ELECTRICAL ENGINEERING
Info Detail Spesifik: -
Pernyataan Tanggungjawab: deliza

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FULLTEXT: Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor drive

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