Constrained Dynamic Systems Estimation Based on Adaptive Particle Filter
Joint Authors
Xu, Bao-guo
Xiong, Weili
Xue, Mingchen
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-11
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
For the state estimation problem, Bayesian approach provides the most general formulation.
However, most existing Bayesian estimators for dynamic systems do not take constraints into account, or rely on specific approximations.
Such approximations and ignorance of constraints may reduce the accuracy of estimation.
In this paper, a new methodology for the states estimation of constrained systems with nonlinear model and non-Gaussian uncertainty which are commonly encountered in practice is proposed in the framework of particles filter.
The main feature of this method is that constrained problems are handled well by a sample size test and two particles handling strategies.
Simulation results show that the proposed method can outperform particles filter and other two existing algorithms in terms of accuracy and computational time.
American Psychological Association (APA)
Xiong, Weili& Xue, Mingchen& Xu, Bao-guo. 2014. Constrained Dynamic Systems Estimation Based on Adaptive Particle Filter. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-483132
Modern Language Association (MLA)
Xiong, Weili…[et al.]. Constrained Dynamic Systems Estimation Based on Adaptive Particle Filter. Mathematical Problems in Engineering No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-483132
American Medical Association (AMA)
Xiong, Weili& Xue, Mingchen& Xu, Bao-guo. Constrained Dynamic Systems Estimation Based on Adaptive Particle Filter. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-483132
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-483132