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A fuzzy logic based power system stabilizer with learning ability

机译:具有学习能力的基于模糊逻辑的电力系统稳定器

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摘要

A fuzzy logic-based power system stabilizer (PSS) with learning ability is proposed in this paper. The proposed PSS employs a multilayer adaptive network. The network is trained directly from the input and the output of the generating unit. The algorithm combines the advantages of artificial neural networks (ANNs) and fuzzy logic control (FLC) schemes. Studies show that the proposed adaptive network-based fuzzy logic PSS (ANF PSS) can provide good damping of power systems over a wide range of operating conditions and improve the dynamic performance of the power system.
机译:提出了一种具有学习能力的基于模糊逻辑的电力系统稳定器(PSS)。提出的PSS采用多层自适应网络。直接从生成单元的输入和输出中训练网络。该算法结合了人工神经网络(ANN)和模糊逻辑控制(FLC)方案的优势。研究表明,所提出的基于自适应网络的模糊逻辑PSS(ANF PSS)可以在广泛的工作条件下为电力系统提供良好的阻尼,并改善电力系统的动态性能。

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