MultiPDF particle filtering in state estimation of nonlinear objects
Autor: | Joanna Zietkiewicz, Marek Retinger, Wojciech Giernacki, Jacek Michalski, Piotr Kozierski |
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Rok vydání: | 2021 |
Předmět: |
Dynamical systems theory
Particle number Computer science Applied Mathematics Mechanical Engineering Computation Aerospace Engineering Ocean Engineering Nonlinear system Acceleration Quality (physics) Control and Systems Engineering State (computer science) Electrical and Electronic Engineering Particle filter Algorithm |
Zdroj: | Nonlinear Dynamics. 106:2165-2182 |
ISSN: | 1573-269X 0924-090X |
Popis: | This paper presents a new particle filter algorithm (MultiPDF) for state estimation of nonlinear systems. The proposed method is a modification of the standard particle filter approach. Due to the strong need for the acceleration of calculations and an improvement in the estimation quality of state estimation, the authors propose a method which enables one to divide the main particle filter into smaller sub-filters with an accordingly smaller number of particles for each one of them. The algorithm has been implemented for various numbers of particles and subordinate parallel filters. Estimation quality has been checked for nine nonlinear objects (both one- and multidimensional) and evaluated through the quality index, average root-mean-squared error. The computation time of the particle filter algorithm for several hardware configurations has been compared. Based on the obtained results, it can be concluded that, besides the computation acceleration, the parallelization of the particle filter’s operation also improves the estimation quality. |
Databáze: | OpenAIRE |
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