Title :
Chaotic synchronization of Lorenz system using Unscented Kalman Filter
Author :
Nosrati, K. ; Azemi, A. ; Pariz, N. ; Shokouhi-R, A.
Author_Institution :
Electr. Eng., Ferdowsi Univ. of Mashhad, Mashhad, Iran
Abstract :
In this paper we present chaotic synchronization of a Lorenz system using Unscented Kalman Filter (UKF). The UKF has shown to produce better results, than Extended Kalman Filter (EKF), without performing potentially ill-conditioned numerical calculations and linearly approximating the evolution of the state vector covariance. The chaotic synchronization is implemented in the presence of state and measurement noises. Simulation results reveal the superior performance of UKF over EKF for this case.
Keywords :
Kalman filters; chaos; covariance analysis; noise measurement; nonlinear systems; synchronisation; Lorenz system; chaotic synchronization; extended Kalman filter; measurement noise; state vector covariance; unscented Kalman filter; Accuracy; Chaos; Estimation; Kalman filters; Mathematical model; Noise measurement; Synchronization; Chaos Synchronization; Extended Kalman Filter; Lorenz System; Unscented Kalman Filter;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968301
