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A parameter estimation and filtering method of chaotic system based on particle filter

被引：0
|
作者：
Li, Guo-Hui [1 ,2 ]
Li, Ya-An [1 ]
Yang, Hong [1 ,2 ]
机构：
[1] School of Marine Engineering, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China
[2] School of Electronic and Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, Shaanxi, China
来源：
Binggong Xuebao/Acta Armamentarii | 2012年 / 33卷 / 12期
关键词：
Bandpass filters - Chaotic systems - Parameter estimation - Automation - Monte Carlo methods;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The parameter estimation of chaotic system is a premise of system control and synchronization. In view of chaotic system's characteristics, such as sensitivity to initial condition, long-term unpredictability and so on, a filter applying to chaotic system was proposed based on chaotic system state space theory and particle filter (PF) theory. In a superimposed noise conditions, the parameter estimation and filtering of Lorenz chaotic system were simulated and analyzed. The simulation results show the proposed filtering algorithm is better than a chaotic system parameter estimation and filtering method based on extended Kalman filter (EKF) in bias estimates, and is an effective method for estimating the parameters of chaotic system and filter.
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页码：1504 / 1509
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