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Linear Control of a Nonlinear Aerospace System via Extended Dynamic Mode Decomposition
AIAA SCITECH 2022 Forum, 2022The 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, Nicholas +5 more
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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.
Jadranko Matuško +2 more
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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.
Jadranko Matuško +2 more
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Higher Order Extended Dynamic Mode Decomposition Based on the Structured Total Least Squares
SIAM Journal on Scientific Computing, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ding, Weiyang, Li, Jie
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Symbolic extended dynamic mode decomposition
Chaos: An Interdisciplinary Journal of Nonlinear ScienceIn this paper, we present a new method of performing extended dynamic mode decomposition (EDMD) on systems, which admit a symbolic representation. EDMD generates estimates of the Koopman operator, K, for a dynamical system by defining a dictionary of observables on the space and producing an estimate, Km, which is restricted to be invariant on the span
Connor Kennedy +2 more
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Extended Dynamic Mode Decomposition with Invertible Dictionary Learning
Neural NetworksThe Koopman operator has received attention for providing a potentially global linearization representation of the nonlinear dynamical system. To estimate or control the original system, the invertibility problem is introduced into the data-driven modeling, i.e., the observables are required to be reconstructed the original system's states.
Yuhong Jin, Lei Hou, Shun Zhong
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Dimension of Lift and Numerical Stability in Extended Dynamic Mode Decomposition
T. Hasebe, Kenji Uchiyama, Kai Masuda
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2019 American Control Conference (ACC), 2019
This paper presents a data-driven method to find a finite-dimensional approximation for the Koopman operator using noisy data. The proposed method is a modification of Extended Dynamic Mode Decomposition which finds an approximation for the projection of the Koopman operator on a subspace spanned by a predefined dictionary of functions.
Masih Haseli, Jorge E. Cortes
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This paper presents a data-driven method to find a finite-dimensional approximation for the Koopman operator using noisy data. The proposed method is a modification of Extended Dynamic Mode Decomposition which finds an approximation for the projection of the Koopman operator on a subspace spanned by a predefined dictionary of functions.
Masih Haseli, Jorge E. Cortes
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Journal of Sound and Vibration, 2013
Abstract A synchrosqueezed wavelet transform combined by wavelet analysis and time–frequency reallocation method was recently developed to improve the quality of time–frequency representation and construct the components of a signal. However, the quality of this transform highly depends on the parameters of wavelet functions.
Jing-Liang Liu +2 more
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Abstract A synchrosqueezed wavelet transform combined by wavelet analysis and time–frequency reallocation method was recently developed to improve the quality of time–frequency representation and construct the components of a signal. However, the quality of this transform highly depends on the parameters of wavelet functions.
Jing-Liang Liu +2 more
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Investigation of Tightening Torque in Bolted Joints Using the Extended Dynamic Mode Decomposition
Guilherme Mendes Santana +3 more
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