Results 51 to 60 of about 780 (160)
Optimality Deviation using the Koopman Operator
CoRRThis paper investigates the impact of approximation error in data-driven optimal control problem of nonlinear systems while using the Koopman operator. While the Koopman operator enables a simplified representation of nonlinear dynamics through a lifted state space, the presence of approximation error inevitably leads to deviations in the computed ...
Yicheng Lin +4 more
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Data-Driven Dynamic State Estimation Framework Using a Koopman Operator-Based Linear Predictor
IEEE AccessDynamic state estimation (DSE) is a fundamental task in many fields, including control systems, robotics, and signal processing. Traditional DSE methods, which rely on mathematical models to describe system dynamics, are often limited in their ...
Deyou Yang +4 more
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Glocal Hypergradient Estimation with Koopman Operator
CoRRGradient-based hyperparameter optimization methods update hyperparameters using hypergradients, gradients of a meta criterion with respect to hyperparameters. Previous research used two distinct update strategies: optimizing hyperparameters using global hypergradients obtained after completing model training or local hypergradients derived after every ...
Ryuichiro Hataya, Yoshinobu Kawahara
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Physics Informed Fully Embedded Koopman Operator-based Optimal Control of Two-Link Robotic System [PDF]
Modeling, Identification and ControlThis paper presents a data-driven framework utilising neural networks to approximate the Koopman operator for a discrete-time representation of an electrically actuated two-link mechanical system, enabling the application of linear control techniques.
Jeppe H. Andersen +3 more
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Functional dimensionality of Koopman eigenfunction space
Results in Applied MathematicsThis work presents the general form solution of Koopman Partial Differential Equation for an autonomous system of N ordinary differential equations. We identify a domain in RN for which any number in the complex plane is an eigenvalue of the Koopman ...
Ido Cohen +2 more
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Koopman Explicit Model Following Control Framework for a Robotic Manipulator
IEEE AccessRobotic manipulators have nonlinear and coupled dynamics, and this situation makes accurate modeling and control difficult under parameter uncertainties and external effects.
Oguz Kaan Hancioglu, Mehmet Onder Efe
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Uncertainty Quantification of Autoencoder-Based Koopman Operator
2024 American Control Conference (ACC)6 pages, 3 ...
Jin Sung Kim +2 more
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Nonparametric Control Koopman Operators [PDF]
IEEE Transactions on Automatic ControlThis paper presents a novel Koopman composition operator representation framework for control systems in reproducing kernel Hilbert spaces (RKHSs) that is free of explicit dictionary or input parametrizations. By establishing fundamental equivalences between different model representations, we are able to close the gap of control system operator ...
Bevanda, Petar +5 more
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Koopman Operator, Geometry, and Learning
, 2020 We provide a framework for learning of dynamical systems rooted in the concept of representations and Koopman operators. The interplay between the two leads to the full description of systems that can be represented linearly in a finite dimension, based on the properties of the Koopman operator spectrum.
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MathematicsSome chemical reactors exhibit coupled dynamics with multiple equilibrium points and strong nonlinearities. The accurate modeling of these dynamics is crucial to optimal control and increasing the reactor’s economic performance. While neural networks can
Mustapha Kamel Khaldi +5 more
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