Results 161 to 170 of about 212,072 (202)

Observability of Koopman Representations and Output Canonical Extended Dynamic Mode Decomposition

2024 IEEE 63rd Conference on Decision and Control (CDC)
The Koopman operator has gained considerable attention due to its ability to represent a nonlinear system as a high-dimensional linear system through nonlinear lifting of the state space.
Hyunsang Park, Inseok Hwang
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Higher Order Extended Dynamic Mode Decomposition Based on the Structured Total Least Squares

SIAM Journal on Scientific Computing, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ding, Weiyang, Li, Jie
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Data-Driven Approximation of Gene Regulatory Networks Using Extended Dynamic Mode Decomposition

2024 China Automation Congress (CAC)
This paper addresses the data-driven modeling problem of a class of gene regulatory networks. Utilizing the Koopman operator theory, the study applies the extended dynamic mode decomposition (EDMD) method to linearize a high-dimensional nonlinear ...
Haojie Lin, Wenju Hu, Xuyang Lou, Yingying Wang   +3 more
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An Extended Dynamic Mode Decomposition Rolling Prediction Method for VSC-HVDC System

2025 IEEE International Conference on Power Systems and Smart Grid Technologies (PSSGT)
Power systems with high penetration of renewable energy sources often experience significant frequency deviations and severe oscillations due to reduced inertia and weak damping.
Chenguang Li, Weiyu Wang, Yijia Cao, J. Li, Zhilin Yang   +4 more
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Model predictive control of vehicle dynamics based on the Koopman operator with extended dynamic mode decomposition

2021 22nd IEEE International Conference on Industrial Technology (ICIT), 2021
The control of vehicle dynamics is a very demanding task due to the complex nonlinear tire characteristics and the coupled lateral and longitudinal dynamics of the vehicle. When designing a Model Predictive Controller (MPC) for vehicle dynamics, this can lead to a non- convex optimization problem.
Švec, Marko, Ileš, Šandor, Matuško, Jadranko   +2 more
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Investigation of Tightening Torque in Bolted Joints Using the Extended Dynamic Mode Decomposition

Proceedings of the XX International Symposium on Dynamic Problems of Mechanics
Guilherme Mendes Santana, Daniely Amorim das Neves, Samuel da Silva, Adriano Todorovic Fabro   +3 more
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Linear Control of a Nonlinear Aerospace System via Extended Dynamic Mode Decomposition

AIAA SCITECH 2022 Forum, 2022
The linear representation of nonlinear systems dynamics has a tremendous potential to enable the estimation, prediction, and control of nonlinear systems using standard and well-known methodologies available for linear systems. Numerical algorithms such as the Extended Dynamic Mode Decomposition (EDMD) has been recently proposed to identify, from ...
Cartocci N., Monarca A., Costante G., Fravolini M. L., Dogan K. M., Yucelen T.   +5 more
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Bayesian Hankel Extended Dynamic Mode Decomposition for System Identification of High-Speed Planing Hulls

SNAME International Conference on Fast Sea Technology
Abstract This study explores Bayesian Hankel extended Dynamic Mode Decomposition with control (BHeDMDc) as data-driven, model-free methods for predicting the response of the Generic Prismatic Planing Hull (GPPH) in wave conditions. This approach decomposes complex vessel dynamics into spatial-temporal coherent modes,
Giorgio Palma, Andrea Serani, Matteo Diez, Christian Milano, Zhaoyuan Wang, Sungtek Park, Deniz Ozturk Sarigul, Frederick Stern   +7 more
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Dimension of Lift and Numerical Stability in Extended Dynamic Mode Decomposition

2025 SICE International Symposium on Control Systems (SICE ISCS)
Extended Dynamic Mode Decomposition (EDMD), a data-driven modeling method, has gained interest because the method can construct an accurate linear model using the lifting function.
Tatsuki Hasebe, Kenji Uchiyama, Kai Masuda   +2 more
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Multilayer Extended Dynamic Mode Decomposition for Coupled Van der Pol Oscillators

2024 28th International Conference on Methods and Models in Automation and Robotics (MMAR)
Extended dynamic mode decomposition (EDMD), which is the data-driven method based on the Koopman operator approach, is one of the valuable methods when treating nonlinear dynamical systems.
Tatsuki Hasebe, Kenji Uchiyama, Kai Masuda   +2 more
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