Title :
Chaos system filter on state-space model and EKF
Author :
Yong, Chen ; Xia, Liu ; Qi, Huang ; Changhua, Zhang
Author_Institution :
Sch. of Autom. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
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.
Keywords :
Kalman filters; chaos; nonlinear control systems; nonlinear filters; parameter estimation; state estimation; state-space methods; EKF; Lorenz system; MATLAB; chaos system filter; nonlinear system; parameter estimation; state estimation; state-space model; Chaos; Control systems; Filtering algorithms; Filtering theory; Filters; MATLAB; Mathematical model; Nonlinear systems; State estimation; State-space methods; Chaos system; EKF; Sstate estimation; Sstate space;
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
DOI :
10.1109/ICAL.2009.5262767