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A generalized analytical tuning approach for model predictive controlled grid-tied converters under wide range of grid inductance variation

Khan, Waqar A., Ebrahimian, Armin, Iman Hosseini, S. S., Abarzadeh, Mostafa, Weise, Nathan et Al-Haddad, Kamal. 2022. « A generalized analytical tuning approach for model predictive controlled grid-tied converters under wide range of grid inductance variation ». IEEE Access, vol. 10. pp. 108261-108275.
Compte des citations dans Scopus : 1.

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Résumé

In medium-high power applications, the LCL is the preferred filter topology to attain efficient power conversion. The filter provides a high damping attenuation of -60 dB/decade above the resonance frequency at the cost of a higher order plant, complex parameter design, and, increased vulnerability to un-modeled disturbances. Recently, model predictive control applied to power electronic converters has experienced great interest from researchers. The technique is tailored to the control of complex MIMO systems such as the LCL filter as it allows simultaneous regulation of several state-variables via a user defined cost function. However, the tuning of weighting factors (WFs) within the cost function is not trivial, and in most cases employs an empirical procedure. This paper presents an analytical procedure for tuning of WFs for indirect model predictive current controlled grid-tied converters. The method is based on using analytical closed-form expressions, that relate closed-loop poles of the filter with WFs via physical plant parameters. The presented expressions generalize the tuning of WFs to any arbitrary LCL design. The proposed method is validated by hardware-in-the-loop simulations conducted on PLECS RTBOX 3. Through experimental testing, it is shown that the controller is robust against a wide range of grid impedance variation.

Type de document: Article publié dans une revue, révisé par les pairs
Professeur:
Professeur
Al Haddad, Kamal
Affiliation: Génie électrique
Date de dépôt: 02 nov. 2022 19:13
Dernière modification: 15 nov. 2022 14:25
URI: https://espace2.etsmtl.ca/id/eprint/25704

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