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兵工学报 ›› 2012, Vol. 33 ›› Issue (12): 1504-1509.doi: 10.3969/j.issn.1000-1093.2012.12.016

• 论文 • 上一篇    下一篇

基于粒子滤波的混沌系统参数估计和滤波方法

李国辉1,2, 李亚安1, 杨宏1,2   

  1. (1.西北工业大学 航海学院, 陕西 西安 710072; 2.西安邮电大学 电子工程学院, 陕西 西安 710121)
  • 收稿日期:2011-12-14 修回日期:2011-12-14 上线日期:2014-01-09
  • 作者简介:李国辉(1978—),男,副教授
  • 基金资助:
    国家自然科学基金项目(51179157);陕西省教育厅专项科研计划项目(2010JK823、2012JK0493); 西安邮电大学青年教师科研基金(ZL2010-22、ZL2011-07)

A Parameter Estimation and Filtering Method of Chaotic System Based on Particle Filter

LI Guo-hui1,2, LI Ya-an1, YANG Hong1,2   

  1. (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)
  • Received:2011-12-14 Revised:2011-12-14 Online:2014-01-09

摘要: 混沌系统的参数估计是混沌系统控制和同步的前提。鉴于混沌系统具有初值敏感性、不能长期预测等特点,提出了一种基于粒子滤波(PF)的混沌系统参数估计和滤波方法,并将其用于Lorenz混沌系统的参数估计和滤波,在叠加噪声情况下对混沌系统进行仿真分析。结果表明,文中提出的滤波方法在估计偏差方面优于基于扩展卡尔曼滤波(EKF)的混沌系统参数估计和滤波方法,对混沌系统的参数估计和滤波是一种有效的方法。

关键词: 自动控制技术, 混沌系统, 粒子滤波, 扩展卡尔曼滤波器, 滤波

Abstract: 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.

Key words: automatic control technology, chaotic system, particle filter, extended Kalman filter, filter

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