References & Citations
Nonlinear Sciences > Adaptation and Self-Organizing Systems
Title: Data-driven stability analysis of a chaotic time-delayed system
(Submitted on 14 Feb 2023)
Abstract: Systems with time-delayed chaotic dynamics are common in nature, from control theory to aeronautical propulsion. The overarching objective of this paper is to compute the stability properties of a chaotic dynamical system, which is time-delayed. The stability analysis is based only on data. We employ the echo state network (ESN), a type of recurrent neural network, and train it on timeseries of a prototypical time-delayed nonlinear thermoacoustic system. By running the trained ESN autonomously, we show that it can reproduce (i) the long-term statistics of the thermoacoustic system's variables, (ii) the physical portion of the Lyapunov spectrum, and (iii) the statistics of the finite-time Lyapunov exponents. This work opens up the possibility to infer stability properties of time-delayed systems from experimental observations.
Submission history
From: Georgios Margazoglou Ph.D. [view email][v1] Tue, 14 Feb 2023 19:39:27 GMT (485kb,D)
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