Parameter Identification of Chaotic Systems Based on High-Order Correlation Computations

doi:10.13190/j.jbupt.2019-021

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2019, Vol. 42 ›› Issue (5): 15-21.doi: 10.13190/j.jbupt.2019-021

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Parameter Identification of Chaotic Systems Based on High-Order Correlation Computations

WU Lin-chong¹, YAN Zi-xiang², XIAO Jing-hua¹

1. School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. School of Physics, Peking University, Beijing 100871, China

Received:2019-02-07 Online:2019-10-28 Published:2019-11-25

Abstract

Abstract: In order to reduce the influence of system nonlinearity and noise on the effect of parameter identification, the high-order correlation computations (HOCC) with missing variables and noise is used to identify the dynamic parameters of real chaotic Chua's circuit, based on both simulation and experimental data of a single chua's circuit and a coupled chua's circuit. The results showed that the relative errors between identifications and calibration parameters of the experiments can be controlled within 20%, which means HOCC not only has good robustness to noise but also solves the problem produced by the missing data of the current of inductance. This work provided a benchmark for the measurement of instrument parameters of Chua's circuit, and could further apply on the parameter identification of other complicated networks.

Key words: missing variables, high-order correlation computations, Chua's circuit, parameter identification, robustness

CLC Number:

O415.5

WU Lin-chong, YAN Zi-xiang, XIAO Jing-hua. Parameter Identification of Chaotic Systems Based on High-Order Correlation Computations[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(5): 15-21.

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Parameter Identification of Chaotic Systems Based on High-Order Correlation Computations

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