Kermadi, Mostefa and Rebai, Aissa and Baghli, Lotfi and Mesbahi, Nadhir and Mekhilef, Saad and Mubin, Marizan and Mokhlis, Hazlie (2024) Model-Free Predictive Current Controller for Voltage Source Inverters Using ARX Model and Recursive Least Squares. IEEE Transactions on Circuits and Systems II-Express Briefs, 71 (5). pp. 2619-2623. ISSN 1549-7747, DOI https://doi.org/10.1109/TCSII.2024.3349501.
Full text not available from this repository.Abstract
This brief proposes a model-free deadbeat predictive controller (MF-DPC) for voltage source inverters. The proposed control scheme does not require knowledge of the system parameters for its correct operation. This is performed using an auto-regressive with exogenous input (ARX) model with a recursive least squares (RLS) estimation algorithm for parameter identification to represent the physical system. A state-space predictive model using the identified parameters and the past data measurements is established to calculate the inverter voltage reference using the deadbeat control principle and generate it using space vector modulation (SVM) allowing fixed-switching operation. In addition, the inherent sensitivity of the deadbeat controller to parameter mismatches is avoided. Simulation and experimental results confirm the validity of the proposed model-free control approach in terms of tracking accuracy and waveform quality.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Predictive models; Inverters; Mathematical models; Load modeling; Integrated circuit modeling; Predictive control; Control systems; Deadbeat (DB) predictive control; model-free; data-driven; recursive least square (RLS) identification; auto-regressive with exogenous input (ARX) model |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 30 Sep 2024 06:54 |
| Last Modified: | 30 Sep 2024 06:54 |
| URI: | http://eprints.um.edu.my/id/eprint/45266 |
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