WSEAS Transactions on Systems and Control
Print ISSN: 1991-8763, E-ISSN: 2224-2856
Volume 10, 2015
Robust Real-Time Chaos Detection from Measurement Data
Authors: ,
Abstract: The ability to distinguish between chaotic from regular dynamics is not a trivial task and the fact that noise cannot be avoided in real physical systems makes the problem even more challenging. Chaos becomes highly unpredictable after a very short period of time as a random-like motion that traditional detection techniques may fail, especially when measurement noises are taken into consideration. The present paper proposes a new algorithm to detect chaotic modes automatically (without any model), in real-time and in the presence of noise. The key idea behind the detection lies in the fact that a single component of a chaotic trajectory tends to exhibit an infinite number of local maxima at different time-instants. Using an auxiliary system acting as a denoiser and resorting to simple mathematical operations, it is established a parameter that characterizes the type of motion based on a specified threshold. Numerical simulations are presented to validate the effectiveness and robustness using three applications: a butterfly-shaped system identical to the celebrated Lorenz system; and two aerospace systems related to the attitude motion of spacecraft. The results show that the distinction is very clear and the detector is effective even for relatively low Signal-to-Noise Ratios. The proposed detector is easily-implementable and very efficient from the computational viewpoint as opposed to other tools of chaos detection.
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Pages: 735-751
WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 10, 2015, Art. #79