An Efficient Neurocontroller Position Method for PMSM Drive System

O. Aguilar-Mejía, H. M. Popocatl, J.M. Garcia-Morales, C. O. Castillo-Ibarra, A. Valderrábano‐González
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Abstract

PMSM has been widely used in high-precision variable-speed applications, however, the control scheme demands normally a high dynamic performance under several operating contidions. Due to the non-linear nature of the PMSM, the use of an adaptive controller based on B-spline neural networks is proposed to determine the control signals. The proposed control technique through neural networks exhibits the best performance because it can be adapted to each operating condition, demanding low computational cost for an online operation, and considering non-linearities of the system. The performance of the proposed controller is evaluated in the presence of uncertainties. The results are compared with the conventional PI controller, optimized using whale optimization algorithm.
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一种高效的PMSM驱动系统神经控制器定位方法
永磁同步电机已广泛应用于高精度变速应用,但其控制方案通常要求在多种工况下具有较高的动态性能。针对永磁同步电机的非线性特性,提出了一种基于b样条神经网络的自适应控制器来确定控制信号。所提出的神经网络控制技术由于能适应各种工况、在线运行计算成本低、考虑系统的非线性等特点,表现出最佳的控制性能。在存在不确定性的情况下,对所提控制器的性能进行了评估。结果与传统PI控制器进行了比较,并采用鲸鱼优化算法进行了优化。
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