中文摘要：

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。

英文摘要：

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.