Electrical signals parameter estimation using adaptive filtering: A comparative study

This paper presents the implementation of adaptive LMS, RLS and Kalman filters, for real time estimation of magnitude and phase angle of distorted electrical signals. The filters performance is evaluated by means of the steady-state error, the settling time, among others, through simulations in MATL...

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Bibliographic Details
Published in:	2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA) pp. 745 - 750
Main Authors:	Paez, Idania S Diaz, Pico, Hugo Ortiz, Villalobos, Maria A Mantilla, Suarez, Johann F Petit
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-11-2010
Subjects:	Adaptive algorithms Adaptive filters Electrical signals parameters estimation Equations Filtering algorithms Kalman filter Kalman filters Least Mean Square filter (LMS) Least squares approximation Mathematical model Real time systems Recursive Least Square filter (RLS)
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Summary:	This paper presents the implementation of adaptive LMS, RLS and Kalman filters, for real time estimation of magnitude and phase angle of distorted electrical signals. The filters performance is evaluated by means of the steady-state error, the settling time, among others, through simulations in MATLAB/Simulink. In addition, adaptive filters are implemented in the DS1104 dSPACE development board to evaluate its performance in real time. The simulation and experimental results are shown to validate the algorithms performance.
DOI:	10.1109/TDC-LA.2010.5762967