A Parameter Estimation and Filtering Method of Chaotic System Based on Particle Filter

doi:10.3969/j.issn.1000-1093.2012.12.016

Abstract

Abstract: 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.

Key words: automatic control technology, chaotic system, particle filter, extended Kalman filter, filter

CLC Number:

TP391

LI Guo-hui, LI Ya-an, YANG Hong. A Parameter Estimation and Filtering Method of Chaotic System Based on Particle Filter[J]. Acta Armamentarii, 2012, 33(12): 1504-1509.

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