Work

Data-Driven Model Identification Using Time Delayed Nonlinear Maps for Systems with Multiple Attractors

Year: 2024

Type: preprint

Abstract: This study presents a method, along with its algorithmic and computational framework implementation, and performance verification for dynamical system identification. The approach incorporates insights from phase space structures, such as attractors and their basins. By understanding these structures, we have improved training and testing strategies for operator learning and system identification. Our method uses time delay and non-linear maps rather than embeddings, enabling the assessment of algorithmic accuracy and expressibility, particularly in systems exhibiting multiple attractors. This method, along with its associated algorithm and computational framework, offers broad applicability across various scientific and engineering domains, providing a useful tool for data-driven characterization of systems with complex nonlinear system dynamics.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2411.10910

Authors: lliopoulos, Athanasios P., Lunasin, Evelyn, Michopoulos, John G., Rodriguez, Steven N., Wiggins, Stephen

Institutions: United States Naval Research Laboratory, United States Naval Academy, University of Bristol

Language: English

Topic: Control Systems and Identification

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: Office of Naval Research, U.S. Naval Academy, U.S. Naval Research Laboratory

OpenAlex ID: W4404570403

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