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Robust particle filter—anti-zero bias modification


[ 1 ] Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | [ 2 ] Instytut Elektrotechniki i Elektroniki Przemysłowej, Wydział Elektryczny, Politechnika Poznańska | [ P ] employee

Year of publication


Published in

International Journal of Robust and Nonlinear Control

Journal year: 2016 | Journal volume: vol. 26 | Journal number: iss. 16

Article type

scientific article

Publication language


  • robust state estimation
  • large measurement errors
  • power system
  • bad data

EN A modification of the particle filter algorithm that allows using it also in cases with incorrect measurements has been presented in the paper. The use of anti-zero bias does not require a large computational effort (a single additional operation for each measurement value), and simultaneously does not deteriorate results for the case of good measurements (if the bias value is not too large). It has been shown that the bias which provides the best estimation quality depends on the particles number. The obtained results have been compared with unscented Kalman filter method with bad measurement data identification. As an object, power system has been used, with main task set as estimation of the state of this system.

Pages (from - to)

3645 - 3661




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