A new computing approach for power signal modeling using fractional adaptive algorithms.
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.
Department of Electronic Engineering, International Islamic University, Islamabad, Pakistan. Electronic address: naveedch835@gmail.com.
Naveed Ishtiaq
NI
Chaudhary
Department of Electronic Engineering, International Islamic University, Islamabad, Pakistan. Electronic address: szubair@iiu.edu.pk.
Syed
S
Zubair
Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock Campus, Attock, Pakistan. Electronic address: rasifzahoor@yahoo.com.
Muhammad Asif Zahoor
MAZ
Raja
Fractional adaptive algorithms; Nonlinear adaptive strategies; Parameter estimation; Power signal; Signal modeling