On-the-fly Surrogation for Complex Nonlinear Dynamics Article Swipe

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E. Javier Olucha , Rajiv R. P. Singh , Amritam Das , Roland Tóth ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2504.00276

High-fidelity models are essential for accurately capturing nonlinear system dynamics. However, simulation of these models is often computationally too expensive and, due to their complexity, they are not directly suitable for analysis, control design or real-time applications. Surrogate modelling techniques seek to construct simplified representations of these systems with minimal complexity, but adequate information on the dynamics given a simulation, analysis or synthesis objective at hand. Despite the widespread availability of system linearizations and the growing computational potential of autograd methods, there is no established approach that systematically exploits them to capture the underlying global nonlinear dynamics. This work proposes a novel surrogate modelling approach that can efficiently build a global representation of the dynamics on-the-fly from local system linearizations without ever explicitly computing a model. Using radial basis function interpolation and the second fundamental theorem of calculus, the surrogate model is only computed at its evaluation, enabling rapid computation for simulation and analysis and seamless incorporation of new linearization data. The efficiency and modelling capabilities of the method are demonstrated on simulation examples.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2504.00276
PDF: https://arxiv.org/pdf/2504.00276
OA Status: green
OpenAlex ID: https://openalex.org/W4417224681

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OpenAlex ID: https://openalex.org/W4417224681

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DOI: https://doi.org/10.48550/arxiv.2504.00276

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Title: On-the-fly Surrogation for Complex Nonlinear Dynamics

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-03-31

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Authors: E. Javier Olucha, Rajiv R. P. Singh, Amritam Das, Roland Tóth

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Landing page: https://arxiv.org/abs/2504.00276

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PDF URL: https://arxiv.org/pdf/2504.00276

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OA status: green

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Cited by: 0

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