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首页> 外文期刊>Industrial Informatics, IEEE Transactions on >Nonlinear Modeling of the Inverse Force Function for the Planar Switched Reluctance Motor Using Sparse Least Squares Support Vector Machines
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Nonlinear Modeling of the Inverse Force Function for the Planar Switched Reluctance Motor Using Sparse Least Squares Support Vector Machines

机译：基于稀疏最小二乘支持向量机的平面开关磁阻电动机反作用力函数的非线性建模

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摘要

In the advanced manufacturing industry, planar switched reluctance motors (PSRMs) have proved to be a promising candidate due to their advantages of high precision, low cost, low heat loss, and ease of manufacture. However, their inverse force function, which provides vital phase current command for precise motion, is highly nonlinear and hard to be accurately modeled. This paper proposes a novel inverse force function using sparse least squares support vector machines (LS-SVMs) to achieve nonlinear modeling for precise motion of a PSRM. The required training and testing sets of sparse LS-SVMs are first obtained from experimental measurement. A sparse LS-SVMs regression is further developed using training set to accurately model the inverse force function. Accordingly, the function is tested via the testing set to assess its feasibility. Finally, the proposed approach is applied to the PSRM system with dSPACE controller for trajectory tracking, and its effectiveness and superior performance are verified through experimental results.
机译：在先进制造业中，平面开关磁阻电机（PSRM）具有高精度，低成本，低热损失和易于制造的优点，已被证明是有前途的候选产品。但是，它们的反作用力函数可提供至关重要的相电流指令以实现精确运动，它是高度非线性的并且很难精确建模。本文提出了一种新颖的反力函数，该函数使用稀疏最小二乘支持向量机（LS-SVM）来实现PSRM精确运动的非线性建模。首先从实验测量中获得所需的稀疏LS-SVM的训练和测试集。使用训练集进一步开发稀疏的LS-SVMs回归，以准确地模拟反作用力函数。因此，通过测试集对功能进行测试以评估其可行性。最后，将该方法应用于带有dSPACE控制器的PSRM系统进行轨迹跟踪，并通过实验结果验证了其有效性和优越的性能。

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