Unscented Kalman filter for frequency and amplitude estimation

Happy Novanda, Pawel Regulski, Francisco M. González-Longatt, Vladimir Terzija

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2011 IEEE PES Trondheim PowerTech
Subtitle of host publicationThe Power of Technology for a Sustainable Society, POWERTECH 2011
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE PES Trondheim PowerTech: The Power of Technology for a Sustainable Society, POWERTECH 2011 - Trondheim, Norway
Duration: 19 Jun 201123 Jun 2011

Publication series

Name2011 IEEE PES Trondheim PowerTech: The Power of Technology for a Sustainable Society, POWERTECH 2011

Conference

Conference2011 IEEE PES Trondheim PowerTech: The Power of Technology for a Sustainable Society, POWERTECH 2011
Country/TerritoryNorway
CityTrondheim
Period19/06/1123/06/11

Keywords

  • amplitude estimation
  • frequency estimation
  • Kalman filters
  • power quality
  • unscented transformation

Fingerprint

Dive into the research topics of 'Unscented Kalman filter for frequency and amplitude estimation'. Together they form a unique fingerprint.

Cite this