A Computationally Efficient Robust Direct Model Predictive Control for Medium Voltage Induction Motor Drives

Long-horizon direct model predictive control (MPC) has pronounced computational complexity and is susceptible to parameter mismatches. To address these issues, this paper proposes a solution that enhances the robustness of long-horizon direct MPC, while keeping its computational complexity at bay. T...

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Bibliographic Details
Published in2021 IEEE Energy Conversion Congress and Exposition (ECCE) pp. 4690 - 4697
Main Authors Tregubov, Andrei, Karamanakos, Petros, Ortombina, Ludovico
Format Conference Proceeding
LanguageEnglish
Published IEEE 10.10.2021
Subjects
Computational modeling
Estimation
Measurement
Medium voltage
Robustness
Switching frequency
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Summary:Long-horizon direct model predictive control (MPC) has pronounced computational complexity and is susceptible to parameter mismatches. To address these issues, this paper proposes a solution that enhances the robustness of long-horizon direct MPC, while keeping its computational complexity at bay. The former is achieved by means of a suitable prediction model of the drive system that enables the effective estimation of the total leakage inductance of the machine. For the latter, the objective function of the MPC problem is formulated such that, even though the drive behavior is computed over a long prediction interval, only a few changes in the candidate switch positions are considered. The effectiveness of the proposed approach is demonstrated with a medium-voltage (MV) drive consisting of a three-level neutral point clamped (NPC) inverter and an induction machine (IM).
ISSN:2329-3748
DOI:10.1109/ECCE47101.2021.9595296