Accurate estimation of power signal frequency is an important requirement for many application areas that include system protection, energy quality monitoring and instrumentation. Though significant efforts have been ...
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Accurate estimation of power signal frequency is an important requirement for many application areas that include system protection, energy quality monitoring and instrumentation. Though significant efforts have been made since long to develop potent algorithms for accurate estimation of power signal frequency, still their accuracy and convergence speed are a challenge under sudden frequency drift and variations. Therefore, this study focuses on a low complexity adaptive linear element filter using quadratic signal model, whose parameters are adjusted using a fast variable step size fuzzy logic-based learning algorithm to provide better convergence and noise rejection properties for the estimation of frequency from noisy and distorted signals. In addition, the new filter has also been implemented on a field programmable gate array hardware and Xilinx 14.2 with Sysgen software for the tracking of dynamic signal parameters in single and three phase power networks. Various numerical and experimental results are addressed for estimation of frequency of time varying sinusoids.
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