Near State Vector Selection-Based Model Predictive Control with Common Mode Voltage Mitigation for a Three-Phase Four-Leg Inverter

Dadu, A.M. and Mekhilef, Saad and Tey, Kok Soon and Seyedmahmoudian, M. and Horan, B. (2017) Near State Vector Selection-Based Model Predictive Control with Common Mode Voltage Mitigation for a Three-Phase Four-Leg Inverter. Energies, 10 (12). p. 2129. ISSN 1996-1073, DOI

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A high computational burden is required in conventional model predictive control, as all of the voltage vectors of a power inverter are used to predict the future behavior of the system. Apart from that, the common mode voltage (CMV) of a three-phase four-leg inverter utilizes up to half of the DC-link voltage due to the use of all of the available voltage vectors. Thus, this paper proposes a near state vector selection-based model predictive control (NSV-MPC) scheme to mitigate the CMV and reduce computational burden. In the proposed technique, only six active voltage vectors are used in the predictive model, and the vectors are selected based on the position of the future reference vector. In every sampling period, the position of the reference current is used to detect the voltage vectors surrounding the reference voltage vector. Besides the six active vectors, one of the zero vectors is also used. The proposed technique is compared with the conventional control scheme in terms of execution time, CMV variation, and load current ripple in both simulation and an experimental setup. The LabVIEW Field programmable gate array rapid prototyping controller is used to validate the proposed control scheme experimentally, and demonstrate that the CMV can be bounded within one-fourth of the DC-link voltage.

Item Type: Article
Uncontrolled Keywords: Common mode voltage; Computational burden and three phase four leg inverter; Execution time; Near state vector selection based model predictive control; Ripple content
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Computer Science & Information Technology
Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 08 Aug 2018 06:21
Last Modified: 25 Oct 2019 05:37

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