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首页> 外文期刊>IEEE transactions on industrial informatics >Online Weighting Factor Optimization by Simplified Simulated Annealing for Finite Set Predictive Control
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Online Weighting Factor Optimization by Simplified Simulated Annealing for Finite Set Predictive Control

机译：有限套装预测控制简化模拟退火的在线加权因子优化

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摘要

Model predictive control brings many advantages and it simplifies the control scheme in power electronics. However, tuning the weighting factor is one of the important open discussions on this topic. There are online and offline methods that have been introduced to select the weighting factor. The online methods are preferred because they are more feasible. In this article, an online weighting factor optimization method based on the simulated annealing algorithm is proposed. The energy of the ripple is used as a convergence criterion. The presented method can be converged in a few steps and it does not impose cumbersome computations. Therefore, the optimal voltage will be identical for a range of the weighting factor. Furthermore, the used search algorithm is parameter independent. The proposed method is implemented for an induction motor but it is also applicable for other applications. The proposed method is validated by the experimental tests.
机译：模型预测控制带来了许多优点，简化了电力电子设备的控制方案。但是，调整加权因子是本主题的重要开放讨论之一。已引入的在线和离线方法选择加权因子。在线方法是首选，因为它们更加可行。在本文中，提出了一种基于模拟退火算法的在线加权因子优化方法。纹波的能量用作收敛标准。呈现的方法可以在几个步骤中融合，并且它不会施加麻烦的计算。因此，对于加权因子的范围，最佳电压将是相同的。此外，使用的搜索算法是独立的参数。所提出的方法用于感应电动机，但它也适用于其他应用。所提出的方法是通过实验测试验证的。

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