DocumentCode :
3302443
Title :
Unscented Kalman Filter for frequency and amplitude estimation
Author :
Novanda, H. ; Regulski, P. ; Gonzalez-Longatt, Francisco M. ; Terzija, Vladimir
Author_Institution :
Sch. of Electr. & Electron. Eng., Univ. of Manchester, Manchester, UK
fYear :
2011
fDate :
19-23 June 2011
Firstpage :
1
Lastpage :
6
Abstract :
This paper introduces a new digital signal processing algorithm for frequency and amplitude estimation based on Unscented Kalman Filter (UKF). The results of computer simulated and realistic synthetic data tests are presented. The initial parameters used during the tests were chosen carefully using an established parameter estimation method, the Self Tuning Least Square (STLS). It is concluded that the proposed algorithm is simple, efficient and has low computational demands compare to STLS which makes the UKF a very promising method in next generation of power quality monitoring devices.
Keywords :
Kalman filters; amplitude estimation; digital signal processing chips; frequency estimation; least squares approximations; power supply quality; power system parameter estimation; STLS; UKF; amplitude estimation; digital signal processing algorithm; frequency estimation; parameter estimation method; power quality monitoring device; realistic synthetic data test; self tuning least square; unscented Kalman filter; Estimation; Frequency estimation; Kalman filters; Noise; Power quality; Power system dynamics; Signal processing algorithms; Kalman filters; amplitude estimation; frequency estimation; power quality; unscented transformation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech, 2011 IEEE Trondheim
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-8419-5
Electronic_ISBN :
978-1-4244-8417-1
Type :
conf
DOI :
10.1109/PTC.2011.6019414
Filename :
6019414
Link To Document :
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