A novel low‐complexity model predictive control for Vienna rectifier

Author:

Sun Zhang1,Jin Weidong1,Wu Fan2,Han Qi3ORCID,Guan Kun3,Ren Junxiao1

Affiliation:

1. School of Electrical Engineering Southwest Jiaotong University Chengdu China

2. School of Automation University of Electronic Science and Technology of China Chengdu China

3. School of Electrical Engineering and Electronic Information Xihua University Chengdu China

Abstract

SummaryA Vienna rectifier is a kind of three‐phase converter with complex operation constraints. Traditional control methods suffer from poor dynamic responses and total harmonic distortion (THD), particularly when operating with adjustable wide‐range power. A novel low‐complexity model predictive control (LC‐MPC) algorithm is proposed based on the optimal switching vector sequence in this paper. First, a model predictive optimization control (MPOC) method is designed to search for the voltage vector sequence and its acting time. Second, the equivalent transformation and coordinate mapping of MPOC are efficiently achieved through the derived correlation factors and lookup table. Supported by the correlation factors, the redundant objective function calculation and repetitive online optimization are eliminated. Meanwhile, the simplified optimal over‐modulation strategy is implemented. Finally, the effectiveness and superiority of the algorithm are verified by comparative experiments. The results show that the proposed LC‐MPC is beneficial in terms of the computation time, dynamic response, over‐modulation, and harmonic content reduction.

Funder

Sichuan Province Science and Technology Support Program

Publisher

Wiley

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Electronic, Optical and Magnetic Materials

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