Data-Driven and Physics-Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence. [PDF]
Adv Sci (Weinh)This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Hui W, Wang Y, Zhang T, Chen Y, Pan M.
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On the Utility of Koopman Operator Theory in Learning Dexterous Manipulation Skills
CoRR, 2023 This work has been accepted for an oral presentation at CORL ...
Yunhai Han +3 more
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Optimizing Neural Networks via Koopman Operator Theory
CoRR, 2020 Koopman operator theory, a powerful framework for discovering the underlying dynamics of nonlinear dynamical systems, was recently shown to be intimately connected with neural network training. In this work, we take the first steps in making use of this connection.
Akshunna S. Dogra, William T. Redman
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Credit assignment for trained neural networks based on Koopman operator theory
Frontiers of Computer Science, 2023 Credit assignment problem of neural networks refers to evaluating the credit of each network component to the final outputs. For an untrained neural network, approaches to tackling it have made great contributions to parameter update and model revolution during the training phase.
Zhen Liang +5 more
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Measurement + Control, 2022 The dynamic modeling and control of omni-directional mobile manipulators (OMM) are challenging since they are highly nonlinear, strongly coupled, and multi-input multi-output uncertainty systems.
Xuehong Zhu +5 more
doaj +1 more source
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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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 Congestion Control of Micro Smart Sensor Networks for Transparent Substations
IEEE Access, 2021 Micro smart sensors and sensor networks are the key bases for building a fully visible, perceptible and controllable transparent substation in power grid.
Ke Zhou +3 more
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Efficient Nonlinear Model Predictive Control of Automated Vehicles
Mathematics, 2022 In this paper, an efficient model predictive control (MPC) of velocity tracking of automated vehicles is proposed, in which a reference signal is given a priori.
Shuyou Yu +5 more
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On the anti-missile interception technique of unpowered phase based on data-driven theory
Mechanics & Industry, 2022 . The anti-missile interception technique of unpowered phase is of much importance in the military field, which depends on the prediction of the missile trajectory and the establishment of the missile model.
Huang Yong, Li Yang
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