Multi-objective control of nine-level anpc converters: a robust and gain-free mpc method

Name: Multi-objective control of nine-level anpc converters: a robust and gain-free mpc method
Author: Harbi, İ., Makhamreh, Hamza, Ahmed, Mostafa, Abdelrahem, M., Heldwein, M., Rodriguez, J., Kennel, R.

İsim	Multi-objective control of nine-level anpc converters: a robust and gain-free mpc method
Yazar	Harbi, İ., Makhamreh, Hamza, Ahmed, Mostafa, Abdelrahem, M., Heldwein, M., Rodriguez, J., Kennel, R.
Basım Tarihi:	2023
Basım Yeri	- IEEE
Konu	Capacitor voltage control, Current control, Model Predictive control, Multilevel converter, Weighting factors
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	979-835039686-7
Kayıt Numarası	0eb5e33a-8c3c-4c52-a1d1-3a4d50226009
Lokasyon	Electrical & Electronics Engineering
Tarih	2023
Notlar	Agencia Nacional de Investigación y Desarrollo
Örnek Metin	Model predictive control (MPC) is a powerful control method for addressing multi-objective control problems, however, one of its main challenges is the cumbersome tuning process of the weighting factors. This paper presents a weighting factorless advanced MPC method for a recently developed nine-level active neutral point clamped (ANPC) converter, which has several advantages over conventional and recent nine-level topologies, such as low number of used switches and flying capacitors (FCs), reduced voltage rating of FCs and high efficiency. The developed MPC method avoids the use of weighting factors while addressing three control objectives: current control, FCs balancing and neutral point (NP) control. Similar to conventional finite-set MPC (FS-MPC), the presented method has high performance in terms of all control objectives. Moreover, this method exhibits enhanced robustness to parameter mismatch compared to the conventional scheme. The effectiveness of this method is validated through experimental testing under various operating conditions. The research demonstrates the potential for this technique to address control problems in ANPC-based converters and highlights its potential for further applications.
DOI	10.1109/PRECEDE57319.2023.10174579

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Multi-objective control of nine-level anpc converters: a robust and gain-free mpc method

Yazar Harbi, İ., Makhamreh, Hamza, Ahmed, Mostafa, Abdelrahem, M., Heldwein, M., Rodriguez, J., Kennel, R.

Basım Tarihi 2023

Basım Yeri - IEEE

Konu Capacitor voltage control, Current control, Model Predictive control, Multilevel converter, Weighting factors

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 979-835039686-7

Kayıt Numarası 0eb5e33a-8c3c-4c52-a1d1-3a4d50226009

Lokasyon Electrical & Electronics Engineering

Tarih 2023

Notlar Agencia Nacional de Investigación y Desarrollo

Örnek Metin Model predictive control (MPC) is a powerful control method for addressing multi-objective control problems, however, one of its main challenges is the cumbersome tuning process of the weighting factors. This paper presents a weighting factorless advanced MPC method for a recently developed nine-level active neutral point clamped (ANPC) converter, which has several advantages over conventional and recent nine-level topologies, such as low number of used switches and flying capacitors (FCs), reduced voltage rating of FCs and high efficiency. The developed MPC method avoids the use of weighting factors while addressing three control objectives: current control, FCs balancing and neutral point (NP) control. Similar to conventional finite-set MPC (FS-MPC), the presented method has high performance in terms of all control objectives. Moreover, this method exhibits enhanced robustness to parameter mismatch compared to the conventional scheme. The effectiveness of this method is validated through experimental testing under various operating conditions. The research demonstrates the potential for this technique to address control problems in ANPC-based converters and highlights its potential for further applications.

DOI 10.1109/PRECEDE57319.2023.10174579