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A GMM-GFM Based Controller for LFC and AVR of a Single Area Power System

机译:基于GMM-GFM基于GMM-GFM的LFC和AVR的单区域电力系统

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In this paper, combination of Generalized Fuzzy Model (GFM) and Gaussian Mixture Model (GMM) based controller is used to determine the optimal parameters of Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) system of single area power system. GFM combines the advantages of Takagi and Sugeno(T-S) and Mamdani -- Larsen (ML) models of fuzzy logic techniques. In the proposed controller, first membership functions are optimized by GMM and then GFM calculates the final output in single iteration i.e. with no recursions. This is highly desirable in power quality problems. The simulations demonstrate the effective and smooth performance of the power system. Comparative analysis is done between controllers based on Proportional and Integral (PI), T-S model, ML model and GMM & GFM model. Simulated results evince the superiority of the proposed hybrid controller.
机译:本文采用了广义模糊模型(GFM)和高斯混合模型(GMM)控制器的组合来确定单区域电力系统负载频率控制(LFC)和自动电压调节器(AVR)系统的最佳参数。 GFM结合了Takagi和Sugeno(T-S)和Mamdani - Larsen(ML)模型的模糊逻辑技术的优点。 在所提出的控制器中,第一个隶属函数由GMM优化,然后GFM计算单次迭代中的最终输出I.。没有递归。 这是在电能质量问题中非常理想的。 该模拟展示了电力系统的有效和平稳性能。 基于比例和积分(PI),T-S型号,ML模型和GMM&amp的控制器之间进行比较分析; GFM模型。 模拟结果Evince Evince提出的混合控制器的优越性。

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