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Model predictive control of three-phase voltage-source converters with improved tracking performance
Hui Wang1, Xida Chen1, Yonglu Liu1
1Hunan Provincial Key Laboratory of Power Electronics Equipment and Grid, School of Automation, Central South University, Changsha 410083, China.
Abstract:
The conventional finite control set-model predictive control (FCS-MPC) has not been completely embraced by the power industry because of large tracking errors and the high required sampling frequency. Therefore, the double-vector-based model predictive control (DVB-MPC), which enfolds the deadbeat control (DBC) theory, has gradually crept into researchers' horizons in recent years. In the universal DVB-MPC (UDVB-MPC) scheme, selecting two operation vectors in a single sector is a major obstacle to achieving satisfactory tracking performance. There is still a biggish error between the synthesized output voltage and the reference value. To alleviate this issue, this paper proposes an improved double-vector-based model predictive control (IDVB-MPC) scheme. The tracking errors are reduced dramatically by adding two extra vectors in adjacent sectors to the candidate set and dividing a sector into eight zones. Then the power fluctuation is reduced and the grid-connected current quality is improved. To verify the effectiveness of the proposed scheme, the simulation and experiment comparisons between UDVB-MPC and IDVB-MPC are carried out. The results show that IDVB-MPC reduces the quantitative tracking errors, the THD of the output currents, and the quantitative active power ripple by about 50%, 20%, and 35% with UDVB-MPC as a benchmark, respectively.
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