MNFIS和其他基于软计算的MPPT技术:比较分析

Jesse Roberts, I. Bhattacharya
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引用次数: 2

摘要

最大功率点跟踪(MPPT)是在电压空间中搜索最优发电,并跟踪最优发电变化的过程。本文介绍了用于此工作的软计算算法的性能分析以及基于性能目标的部署建议。具体来说,模糊逻辑(FL)和人工神经网络(ANN)在直接和间接转换器控制下进行了测试,并与多个指标进行了适应度比较。在此过程中,一种新的算法也被开发出来,被认为是修正神经模糊推理系统(MNFIS)。该算法结合了人工神经网络和人工神经网络的优点,同时减轻了两者的缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MNFIS and other soft computing based MPPT techniques: A comparative analysis
Maximum Power Point Tracking (MPPT) is the process of searching the voltage space for the optimal power generation and tracking the optimum as it changes. This paper presents a performance analysis of soft computing algorithms applied to this endeavor and a deployment recommendation based on performance goals. Specifically, fuzzy logic (FL) and artificial neural networks (ANN) were tested with direct and indirect converter control and compared against multiple metrics for fitness. Along the way a novel algorithm was also developed, deemed the Modified Neuro-Fuzzy Inference System (MNFIS). This algorithm incorporates the strengths of both FL and ANN MPPT while mitigating the weaknesses of either.
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