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Koopman operator theory tutorial covers linear system representation and control

By PulseAugur Editorial · [1 sources] ·

This paper introduces Koopman operator theory, a method for linearly representing complex dynamical systems. It details data-driven techniques like extended dynamic mode decomposition (EDMD) for creating finite-dimensional approximations. The tutorial also covers applications in systems and control, including controller design and simulation studies with accompanying GitHub code. AI

IMPACT Provides a theoretical framework and practical tools for modeling and controlling complex systems, potentially impacting AI applications in robotics and autonomous systems.

RANK_REASON The cluster contains an academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Koopman operator theory tutorial covers linear system representation and control

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The cluster contains an academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Igor Mezi\'c, Jorge Cort\'es, Karl Worthmann, Mircea Lazar, Armin Lederer ·

    Koopman operator theory: fundamentals, control, and applications

    arXiv:2607.01819v1 Announce Type: cross Abstract: The Koopman operator has gained considerable attention due to its ability to provide a global linear representation of highly complex dynamical systems. The operator describes nonlinear dynamics in a linear way through the lens of…

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