A new computing approach for power signal modeling using fractional adaptive algorithms. (May 2017) - Chaudhary, Naveed Ishtiaq; Zubair, Syed; Raja, Muhammad Asif Zahoor
Abstract: Estimating the harmonic parameters is fundamental requirement for signal modelling in a power supply system. In this study, exploration and exploitation in fractional adaptive signal processing (FrASP) is carried out for identification of parameters in power signals. We design FrASP algorithms based on recently introduced variants of generalized least mean square (LMS) adaptive strategies for parameter estimation of the model. The performance of the proposed fractional adaptive schemes is evaluated for number of scenarios based on step size and noise variations. Results of the simulated system for sufficient large number of independent runs validated the reliability and effectiveness of the given methods through different performance measures in terms of mean square error, variance account for, and Nash Sutcliffe efficiency. Highlights: The potential of fractional adaptive algorithms is exploited in the field of power signal modeling. The proposed fractional adaptive schemes are robust for low and high noise variance. Consistent accuracy of the design methodology is verified and validated through the results of statistical analyses. Reliability and effectiveness of the given methods are proven through different performance measures.