基于EKF的新混沌系统滤波方法

Filtering method of new chaotic system based on EKF

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。

A new chaotic system is presented. Some basic dynamical properties are studied. The state esti adapt oneself to the characteristics of the chaos system, such as sensitivity to initial condition, long-term pre dictability. A filter applying to the chaos system is proposed based on chaos system state space theory and ex- tended Kalman filter （EKT） theory. Simulation results show that the proposed algorithm is an effective method to estimate the parameter of chaos systems and filter.