An Innovative Winding Number Method for Nonlinear Dynamical System Characterization

The conventional winding number method is extended in this research to characterize the nonlinear dynamical systems, especially in differentiating partially predictable chaos from strong chaos. On modern robotics’ challenges with increased degrees of freedom, traditional methods like the Lyapunov exponent are insufficient for distinguishing between strong and partially predictable chaos. The proposed methods examine the winding number’s sensitivity with respect to the center and its standard deviations across time sequences to assess predictability and differentiate between different motion types. The Duffing–Van der Pol system is used to show the effectiveness in identifying different chaotic behaviours, offering significant implications for the control of complex robotic systems.

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Published
2024-11-20
DOI
https://doi.org/10.3390/engproc2024076087
Primary Topic
Chaos control and synchronization
Type
article
Field-Weighted Citation Impact
0.00

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article

An Innovative Winding Number Method for Nonlinear Dynamical System Characterization

Shixuan Lu, Liming Dai, Na Jia, Zhengyuan Zhang
Chaos control and synchronization
article

An Innovative Winding Number Method for Nonlinear Dynamical System Characterization

Shixuan Lu, Liming Dai, Na Jia, Zhengyuan Zhang
article en

Abstract

The conventional winding number method is extended in this research to characterize the nonlinear dynamical systems, especially in differentiating partially predictable chaos from strong chaos. On modern robotics’ challenges with increased degrees of freedom, traditional methods like the Lyapunov exponent are insufficient for distinguishing between strong and partially predictable chaos. The proposed methods examine the winding number’s sensitivity with respect to the center and its standard deviations across time sequences to assess predictability and differentiate between different motion types. The Duffing–Van der Pol system is used to show the effectiveness in identifying different chaotic behaviours, offering significant implications for the control of complex robotic systems.

University of Regina (CA)
Natural Sciences and Engineering Research Council of Canada
Affordable and clean energy
Openalex Percentile: Top 80%
Chaos control and synchronization
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