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Neural Network Applications in Power Electronics and Motor Drives—An Introduction and Perspective

机译:神经网络在电力电子和电机驱动器中的应用-简介和展望

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摘要

Artificial intelligence (AI) techniques, particularly the neural networks, are recently having significant impact on power electronics and motor drives. Neural networks have created a new and advancing frontier in power electronics, which is already a complex and multidisciplinary technology that is going through dynamic evolution in the recent years. This paper gives a comprehensive introduction and perspective of neural network applications in the intelligent control and estimation for power electronics and motor drives area. The principal topologies of neural networks that are currently most relevant for applications in power electronics have been reviewed including the detailed description of their properties. Both feedforward and feedback or recurrent architectures have been covered in the description. The application examples that are discussed in this paper include nonlinear function generation, delayless filtering and waveform processing, feedback signal processing of vector drive, space vector PWM of two-level and multilevel inverters, adaptive flux vector estimation, and some of their combination for vector-controlled ac drive. Additional selected applications in the literature are included in the references. From the current trend of the technology, it appears that neural networks will find widespread applications in power electronics and motor drives in future
机译:人工智能(AI)技术,特别是神经网络,最近对电力电子和电机驱动产生了重大影响。神经网络已经在电力电子领域建立了一个新的,前沿的领域,这已经是一项复杂且多学科的技术,并且近年来正在经历动态发展。本文全面介绍了神经网络在电力电子和电机驱动器领域的智能控制和估计中的应用和前景。目前已审查了与电力电子应用最相关的神经网络的主要拓扑,包括其特性的详细描述。描述中既涵盖了前馈架构又包括了反馈架构或递归架构。本文讨论的应用示例包括非线性函数生成,无延迟滤波和波形处理,矢量驱动器的反馈信号处理,两级和多级逆变器的空间矢量PWM,自适应磁通矢量估计及其对矢量的某些组合控制的交流变频器。参考文献中包括文献中其他选定的应用。从该技术的当前趋势来看,似乎神经网络将在未来的电力电子和电机驱动中找到广泛的应用。

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