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A comparative study of adaptive control algorithms in Distribution Static Compensator

机译:配电系统静态补偿器自适应控制算法的比较研究

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In various practical applications such as harmonic current elimination, reactive power compensation and power factor correction many adaptive filtering techniques are used for control of DSTATCOM (Distribution Static Compensator). This paper presents a comparative study of the performance of two weight updating adaptive algorithm LMS (Least Mean Square) based ADALINE (Adaptive Linear Neural Network) and Fuzzy logic based variable step size LMS used for harmonic current detection using VSC (Voltage Source Converter) based DSTATCOM (Distribution Static Compensator). Simulation results in MATLAB environment show that the convergence speed of fuzzy logic based variable step size LMS is much faster and its performance is better than LMS based Adaline under varying load conditions in DSTATCOM application for power quality improvement.
机译:在诸如谐波电流消除,无功功率补偿和功率因数校正之类的各种实际应用中,许多自适应滤波技术用于控制DSTATCOM(分布式静态补偿器)。本文比较了两种基于权重更新的自适应算法LMS(最小均方)ADAMS(自适应线性神经网络)和基于模糊逻辑的可变步长LMS(用于基于VSC(电压源转换器)的谐波电流检测)的性能。 DSTATCOM(配电静态补偿器)。在MATLAB环境下的仿真结果表明,在DSTATCOM应用中,基于模糊逻辑的可变步长LMS的收敛速度要快得多,并且其性能优于基于LMS的Adaline的改进性能,从而改善了电能质量。

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