Comparison of auxiliary and Likelihood Particle Filters for state estimation of dynamical systems

• Autorzy: Michalski J. , Kozierski P. , Ziętkiewicz J.

Identyfikatory

DOI

10.15199/48.2018.12.19

Warianty tytułu

PL

Porównanie filtrów cząsteczkowych, pomocniczego i wiarygodnego, do estymacji stanu systemów dynamicznych

• Języki publikacji: EN

Abstrakty

EN

In this paper, algorithms of the state estimation of dynamical systems, using different types of particle filters, have been presented. Three Particle Filter methods have been used: Bootstrap Filter, Auxiliary Particle Filter and Likelihood Particle Filter. These methods have been applied to two nonlinear objects, with quadratic measurement functions. The results have been additionally compared with the outcome from Kalman filters. Based on the obtained results (5 different quality indices) the estimation methods have been evaluated.

PL

W niniejszej pracy zostały przedstawione algorytmy estymacji stanu układów dynamicznych za pomocą różnych rodzajów filtrów cząsteczkowych. Zaprezentowano trzy metody filtrów cząsteczkowych: algorytm Bootstrap, pomocniczy filtr cząsteczkowy i wiarygodny filtr cząsteczkowy. Metody te zastosowano dla dwóch obiektów nieliniowych o kwadratowych funkcjach pomiarowych. Z filtrami cząsteczkowymi zostały dodatkowo zestawione metody filtru Kalmana. Na podstawie uzyskanych wyników (5 różnych wskaźników jakości) metody estymacji zostały ocenione.

Słowa kluczowe

EN

particle filters; state estimation; dynamical systems; Kalman filters; nonlinear plants

PL

filtr cząsteczkowy; estymacja stanu; układy dynamiczne; filtry Kalmana; obiekty nieliniowe

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2018
• Tom: R. 94, nr 12
• Strony: 86--90
• Opis fizyczny: Bibliogr. 24 poz., tab., wykr.

Twórcy

autor

Michalski J.

• Poznan University of Technology, Faculty of Electrical Engineering, Institute of Control, Robotics and Information Engineering, Division of Control and Robotics, Piotrowo 3a Street, 60-965 Poznań

autor

Kozierski P.

• Poznan University of Technology, Faculty of Computing, Institute of Automation and Robotics, Division of Electronics Systems and Signal Processing and also Faculty of Electrical Engineering, Institute of Control, Robotics and Information Engineering, Division of Control and Robotics, Piotrowo 3a Street, 60-965 Poznań

autor

Ziętkiewicz J.

• Poznan University of Technology, Faculty of Electrical Engineering, Institute of Control, Robotics and Information Engineering, Division of Control and Robotics, Piotrowo 3a Street, 60-965 Poznań

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).