Results 21 to 30 of about 780 (160)
On the Approximability of Koopman-Based Operator Lyapunov Equations
SIAM Journal on Control and Optimization, 2023 Lyapunov equations, Koopman operator, infinite dimensional systems ...
Tobias Breiten, Bernhard Höveler
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Deep Koopman Operator With Control for Nonlinear Systems
IEEE Robotics and Automation Letters, 2022 Recently Koopman operator has become a promising data-driven tool to facilitate real-time control for unknown nonlinear systems. It maps nonlinear systems into equivalent linear systems in embedding space, ready for real-time linear control methods. However, designing an appropriate Koopman embedding function remains a challenging task.
Haojie Shi, Max Q.-H. Meng
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Representer Theorem for Learning Koopman Operators
IEEE Transactions on Automatic Control, 2023 In this work, the problem of learning Koopman operator of a discrete-time autonomous system is considered. The learning problem is formulated as a constrained regularized empirical loss minimization in the infinite-dimensional space of linear operators.
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Identification of the Madden–Julian Oscillation With Data‐Driven Koopman Spectral Analysis
Geophysical Research Letters, 2023 The Madden‐Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, is commonly identified using the realtime multivariate MJO (RMM) index based on joint empirical orthogonal function (EOF) analysis of near‐equatorial upper and ...
Benjamin R. Lintner +3 more
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Complexity, 2018 We consider the application of Koopman theory to nonlinear partial differential equations and data-driven spatio-temporal systems. We demonstrate that the observables chosen for constructing the Koopman operator are critical for enabling an accurate ...
J. Nathan Kutz +2 more
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Stable data‐driven Koopman predictive control: Concentrated solar collector field case study
IET Control Theory & Applications, 2023 Non‐linearity is an inherent feature of practical systems. Although there have been significant advances in the control of nonlinear systems, the proposed methods often require considerable computational resources or rely on local linearization around ...
Tahereh Gholaminejad, Ali Khaki‐Sedigh
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Koopman Operator Applications in Signalized Traffic Systems [PDF]
IEEE Transactions on Intelligent Transportation Systems, 2022 This paper proposes Koopman operator theory and the related algorithm dynamical mode decomposition (DMD) for analysis and control of signalized traffic flow networks. DMD provides a model-free approach for representing complex oscillatory dynamics from measured data, and we study its application to several problems in signalized traffic. We first study
Esther Ling +3 more
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Extending the extended dynamic mode decomposition with latent observables: the latent EDMD framework
Machine Learning: Science and Technology, 2023 Bernard O Koopman proposed an alternative view of dynamical systems based on linear operator theory, in which the time evolution of a dynamical system is analogous to the linear propagation of an infinite-dimensional vector of observables.
Said Ouala +4 more
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Data-Driven Koopman Model Predictive Control for Optimal Operation of High-Speed Trains
IEEE Access, 2021 Automatic train operation systems of high-speed trains are critical to guarantee operational safety, comfort, and parking accuracy. However, implementing optimal automatic operation control is challenging due to the train’s uncertain dynamics and ...
Bin Chen +7 more
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Robot Manipulator Control Using a Robust Data-Driven Method
Fractal and Fractional, 2023 Robotic manipulators with diverse structures find widespread use in both industrial and medical applications. Therefore, designing an appropriate controller is of utmost importance when utilizing such robots.
Mehran Rahmani, Sangram Redkar
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