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Model-Free Predictive Current Control for a SynRM drive based on an effective update of measured current responses

机译:基于测量电流响应的有效更新的SYNRM驱动器无模型预测电流控制

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Predictive current control schemes strongly rely on the knowledge of the plant model. The accuracy of the current prediction could be affected by parameters variation or mismatch, non idealities and other model inadequacies. In Synchronous Reluctance Machine this effect could be particularly critical since its inherent intense iron saturation causes the variation of the indunctances in a wide range. For this reason, the nominal model could be unsuitable for current prediction and could lead to a severe deterioration of the drive performance. In this paper a novel Model-Free Predictive Current Control is presented. The current variations related to the feeding voltage vectors are recorded on-line and stored in a Lookup Table. The current prediction is later obtained by accessing the LUT in the position related to the considered voltage vector. The novelty of this work is the updating method for the Lookup Table. The proposed technique allows reconstructing all the current variations using only the responses related to the three most recent voltage vectors. The result is an improved Model-Free predictive current control in which the reliability of the prediction is guaranteed by the frequent LUT update while always observing the optimal control given by the cost function minimization.
机译:预测电流控制方案强烈依赖于工厂模型的知识。目前预测的准确性可能受参数变化或不匹配,非理想和其他模型的影响。在同步磁阻机中,由于其固有的强态铁饱和度导致诸如宽范围内的鉴定变化,因此这种效果可能是特别关键的。因此,标称模型可能不适合电流预测,并且可能导致驱动性能的严重恶化。在本文中,提出了一种新型无模型预测电流控制。与馈送电压矢量相关的电流变化在线记录并存储在查找表中。稍后通过访问与所考虑的电压矢量相关的位置的LUT获得电流预测。这项工作的新颖性是查找表的更新方法。所提出的技术允许仅使用与三个最近电压矢量相关的响应重建所有电流变化。结果是改进的无模型预测电流控制,其中通过频繁的LUT更新保证预测的可靠性,同时始终观察到由成本函数最小化给出的最佳控制。

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