Chaos System Filter on State-space Model and EKF

被引：0

作者：

Chen Yong ^{[1
]}

Liu Xia ^{[1
]}

Huang Qi ^{[1
]}

Zhang Changhua ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 610054, Peoples R China

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS ( ICAL 2009), VOLS 1-3 | 2009年

关键词：

Chaos system; Sstate space; Sstate estimation; EKF;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

At present, chaos system is currently a hot subject of research in nonlinear system. The state estimation and system trace of chaos system are important in chaos control, but the existing algorithm can't adapt the characteristic of chaos system, quite sensitivity to initial condition and long-term unpredictability. A filter applying to chaos system is proposed on chaos system state space theory and EKF theory, and the states of chaos system are forecasted and estimated on the proposed filtering algorithm. At last, it takes Lorenz system for example, founds the state-space model of Lorenz system and effectively estimated to the three attractor of Lorenz system through the proposed filtering algorithm. Simulation results on MATLAB show the proposed filtering algorithm is a effective method to estimate parameters of chaos system and filter.

引用

页码：1259 / 1263

页数：5

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