系统工程与电子技术

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基于EKF的新混沌系统滤波方法

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
  • 出版日期:2013-09-17 发布日期:2010-01-03

Filtering method of new chaotic system based on EKF

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

  1. 1. College of Marine, Northwestern Polytechnical University, Xi’an 710072, China; 
    2. School of Electronic Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
  • Online:2013-09-17 Published:2010-01-03

摘要:

提出一个新的混沌系统,研究其基本动力学特性。在混沌控制及其应用中,混沌系统的状态估计和滤波是重要的,但现有的滤波算法不能适应混沌的初值敏感性、不能长期预测,提出了一种基于扩展卡尔曼滤波(extended Kalman filter, EKF)的混沌系统参数估计和滤波方法。通过对新混沌系统进行数值仿真,结果表明,这是一种有效的滤波方法。

Abstract:

A new chaotic system is presented. Some basic dynamical properties are studied. The state estimation and filtering of a chaos system are important in chaos control, but the existing filtering algorithm cannot  adapt oneself to the characteristics of the chaos system, such as sensitivity to initial condition, longterm predictability. A filter applying to the chaos system is proposed based on chaos system state space theory and extended Kalman filter (EKF) theory. Simulation results show that the proposed algorithm is an effective method to estimate the parameter of chaos systems and filter.