A Particle Filter Approach to Robust State Estimation for a Class of Nonlinear Systems with Stochastic Parameter Uncertainty
SCIE
SCOPUS
- Title
- A Particle Filter Approach to Robust State Estimation for a Class of Nonlinear Systems with Stochastic Parameter Uncertainty
- Authors
- Kim, S; Won, S
- Date Issued
- 2011-05
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Abstract
- In this paper, we propose a robust state estimation method using a particle filter (PF) for a class of nonlinear systems which have stochastic parameter uncertainties. A robust PF was designed using prediction and correction structure. The proposed PF draws particles from a simple proposal density function and corrects the particles with particle-wise correction gains. We present a method to obtain an error variance of each particle and its upper bound, which is minimized to determine the correction gain. The proposed method is less restrictive on system nonlinearities and noise statistics; moreover, it can be applied regardless of system stability. The effectiveness of the proposed robust PF is illustrated via an example based on Chua's circuit.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/10352
- DOI
- 10.1587/TRANSFUN.E94.A.1194
- ISSN
- 0916-8508
- Article Type
- Article
- Citation
- IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, vol. E94A, no. 5, page. 1194 - 1200, 2011-05
- Files in This Item:
- There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.