Results 41 to 50 of about 758 (209)
Advanced Robotics Research, EarlyView.This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
Neural Koopman forecasting for critical transitions in infrastructure networks
Intelligent Systems with ApplicationsWe develop a data-driven framework for long-term forecasting of stochastic dynamics on evolving networked infrastructure systems using neural approximations of Koopman operators.
Ramen Ghosh
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Automation, 2023 This paper provides the theoretical foundation for the approximation of the regions of attraction in hyperbolic and polynomial systems based on the eigenfunctions deduced from the data-driven approximation of the Koopman operator.
Camilo Garcia-Tenorio +3 more
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Stabilizing RED Using the Koopman Operator
IEEE Signal Processing LettersThe widely used RED (Regularization-by-Denoising) framework uses pretrained denoisers as implicit regularizers for model-based reconstruction. Although RED generally yields high-fidelity reconstructions, the use of black-box denoisers can sometimes lead to instability.
Shraddha Chavan, Kunal N. Chaudhury
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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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Advanced Intelligent Discovery, EarlyView.In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun +8 more
wiley +1 more source
Koopman–von Neumann approach to quantum simulation of nonlinear classical dynamics
Physical Review Research, 2020 Quantum computers can be used to simulate nonlinear non-Hamiltonian classical dynamics on phase space by using the generalized Koopman–von Neumann formulation of classical mechanics.
Ilon Joseph
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Model-Based Control Using Koopman Operators
Robotics: Science and Systems XIII, 2017 This paper explores the application of Koopman operator theory to the control of robotic systems. The operator is introduced as a method to generate data-driven models that have utility for model-based control methods. We then motivate the use of the Koopman operator towards augmenting model-based control.
Abraham, Ian +2 more
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Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
Dynamical systems and complex networks: a Koopman operator perspective
Journal of Physics: ComplexityThe Koopman operator has entered and transformed many research areas over the last years. Although the underlying concept—representing highly nonlinear dynamical systems by infinite-dimensional linear operators—has been known for a long time, the ...
Stefan Klus, Nataša Djurdjevac Conrad
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