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Fix-frequency robust power model predictive control method for three-phase PWM rectifiers under unbalanced grid conditions

机译:不平衡网格条件下三相PWM整流器的固定频率鲁棒功率模型预测控制方法

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摘要

Under unbalanced grid conditions, the controller design of a three-phase pulse width modulation (PWM) rectifier is based on an instantaneous power model. By calculating the current references of the converter according to the instantaneous power model, traditional voltage-oriented control (VOC) methods realize the positive-sequence and negative-sequence active and reactive current control of the converter separately using the proportional-integral (PI) controller. However, due to the inner current loop control structure of the traditional VOC method, it is impossible to realize the regulation of all six power components in a common instantaneous power model under an unbalanced grid. Meanwhile, the control performance of the traditional VOC method with a PI controller is degraded under the circuit parameters uncertainty condition. In this paper, a fixed switching frequency robust power model predictive control method (FRP-MPC) is proposed for three-phase PWM rectifiers under the unbalanced grid condition. The proposed control strategy has a number of advantages. An improved instantaneous power model is used for the fixed switching frequency model predictive controller design under the unbalanced grid condition, which has less power variables than the common instantaneous power model. The robustness of the MPC controller is improved by adding a robust item into the predictive model under circuit parameters uncertainty. Simulation and experiment results verify the effectiveness of the proposed control method.
机译:在不平衡的电网条件下,三相脉冲宽度调制(PWM)整流器的控制器设计基于瞬时功率模型。通过根据瞬时功率模型计算转换器的当前参考,传统的导向控制(VOC)方法使用比例积分(PI)分别地实现转换器的正序和负序和反应电流控制控制器。然而,由于传统VOC方法的内部电流回路控制结构,在不平衡网格下,不可能实现在公共瞬时功率模型中的所有六个功率分量的调节。同时,在电路参数不确定条件下,具有PI控制器的传统VOC方法的控制性能降低。本文提出了一种固定开关稳健功率模型预测控制方法(FRP-MPC),在不平衡网格条件下为三相PWM整流器提出。拟议的控制策略具有许多优势。改进的瞬时功率模型用于在不平衡网格条件下的固定开关频率模型预测控制器设计,其功率变量小于公共瞬时功率模型。通过在电路参数不确定性下将稳健的项目添加到预测模型中,改善了MPC控制器的鲁棒性。仿真和实验结果验证了所提出的控制方法的有效性。

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