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Improvised multi-objective model predictive control of matrix converter using fuzzy logic and space vectors for switching decisions

机译:利用模糊逻辑和空间向量改进了矩阵转换器的多目标模型预测控制,用于切换决策

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摘要

Finite control set model predictive control (FCS-MPC) has lately received noteworthy attention in the control of power converters. Such converters have a finite number of switching states, which ensure a small sample space of predictions and minimum computational burden. Although unanimously popular in most converters, multi-objective FCS-MPC (Mo-FCS-MPC) is a particularly attractive choice in the control of matrix converters (MCs), as it enables attainment of multiple objectives with relative ease. Conventionally, a weighing factor-based approach is undertaken in the implementation of Mo-FCS-MPC wherein a cost-function is framed such that each of its constituent objectives, is assigned a relative weight according to its significance. However, the tuning of weights is empirical in nature and hence tedious. This study proposes an improvised technique for implementing Mo-FCS-MPC in MCs while simultaneously meeting a number of objectives such as load current, source current, and input power factor control. Sector information from space vectors of reference output voltages and reference input currents, coupled with a fuzzy decision-making criterion is used to make the final switching decision, hence eliminating the conventional weighing factor-based approach. The inclusion of space vector modulation into predictive control enhances the quality of both loads as well as source current waveforms.
机译:有限控制集模型预测控制(FCS-MPC)最近在电源转换器控制中接受了值得注意的关注。这种转换器具有有限数量的切换状态,这确保了预测的小样本和最小计算负担。虽然在大多数转换器中一致流行,但多目标FCS-MPC(MO-FCS-MPC)是控制矩阵转换器(MCS)的特别有吸引力的选择,因为它能够以相对容易实现多种目标。传统上,在MO-FCS-MPC的实施中进行了一种基于因子的方法,其中伪造成本函数,使得其每个组成物体的每个组成物体被分配相对重要。然而,重量的调整是实际的本质上,因此乏味。本研究提出了一种用于在MCS中实现MO-FCS-MPC的简易技术,同时满足诸如负载电流,源电流和输入功率因数控制的多个目标。来自参考输出电压的空间矢量的扇区信息和参考输入电流,与模糊决策标准一起耦合来进行最终切换决策,因此消除了基于传统的基于因子的方法。将空间向量调制纳入预测控制增强了两个负载的质量以及源电流波形。

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