Results 271 to 280 of about 1,082,543 (312)

Sparsity Structures for Koopman and Perron--Frobenius Operators

SIAM Journal on Applied Dynamical Systems, 2022
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Schlosser, Corbinian, Korda, Milan
openaire   +2 more sources

SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting

International Conference on Machine Learning
Koopman operator theory provides a framework for nonlinear dynamical system analysis and time-series forecasting by mapping dynamics to a space of real-valued measurement functions, enabling a linear operator representation.
Yitian Zhang, Liheng Ma, Antonios Valkanas, Boris N. Oreshkin, Mark Coates   +4 more
semanticscholar   +1 more source

Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems

arXiv.org
The Koopman operator provides a principled framework for analyzing nonlinear dynamical systems through linear operator theory. Recent advances in dynamic mode decomposition (DMD) have shown that trajectory data can be used to identify dominant modes of a
Minchan Jeong, J. J. Ryu, SeYoung Yun, Gregory W. Wornell   +3 more
semanticscholar   +1 more source

A Koopman Operator-based NMPC Framework for Mobile Robot Navigation under Uncertainty

European Control Conference
Mobile robot navigation can be challenged by system uncertainty. For example, ground friction may vary abruptly causing slipping, and noisy sensor data can lead to inaccurate feedback control.
Xiaobin Zhang, Mohamed Karim Bouafoura, Lu Shi, Konstantinos Karydis   +3 more
semanticscholar   +1 more source

Tensor-Based Koopman Operator and Its Application to Optimal Control Problems

Journal of Guidance Control and Dynamics
The Koopman operator theory provides a global linearization framework for general nonlinear dynamics, offering significant advantages for system analysis and control.
Zhi Xu, Ran Dai, Kathleen C. Howell
semanticscholar   +1 more source

Data‐Driven Modeling With Polytopic Uncertainty and Nonlinear Robust Model Predictive Control Design Using Koopman Operator

International Journal of Robust and Nonlinear Control
Model predictive control (MPC) based on the Koopman operator is an effective data‐driven control method for nonlinear systems. However, modeling errors are almost inevitable when applying the Koopman operator to model the nonlinear systems and influence ...
Zhong Chen, Lihui Cen, Xiaofang Chen, Yongfang Xie, Weihua Gui   +4 more
semanticscholar   +1 more source

Analytical Uncertainty Propagation and Maximum a Posteriori Filtering With the Koopman Operator

IEEE Transactions on Aerospace and Electronic Systems
This article proposes a method to propagate uncertainties undergoing nonlinear dynamics using the Koopman operator (KO). Probability density functions are propagated directly using the Koopman approximation of the solution flow of the system, where the ...
Simone Servadio, Giovanni Lavezzi, Christian Hofmann, Di Wu, Richard Linares   +4 more
semanticscholar   +1 more source

Incorporating ESO into Deep Koopman Operator Modeling for Control of Autonomous Vehicles

IEEE Transactions on Control Systems Technology
Koopman operator theory is a kind of data-driven modeling approach that accurately captures the nonlinearities of mechatronic systems such as vehicles against physics-based methods.
Hao Chen, Chengqi Lv
semanticscholar   +1 more source

The extended Koopmans' theorem Fock operator

International Journal of Quantum Chemistry, 1987
AbstractBy expanding the wave function of a system of N particles in terms of products of functions of one and (N‐1) particles, the one‐particle, nonlocal operator F̂EKT (extended Koopmans' theorem) is determined. It is shown that although this operator is nonhermitian, its eigenvalues and eigenfunctions represent the ionization energies and occupied ...
J. Mauricio O. Matos, Orville W. Day
openaire   +1 more source

Autogeneration of Mission-Oriented Robot Controllers Using Bayesian-Based Koopman Operator

IEEE Transactions on robotics
Model-based robot controllers require customized control-oriented models, involving expert knowledge and trial and error. Remarkably, the Koopman operator enables the control-oriented model identification through the input–output mapping set, breaking ...
Jie Pan, Dongyue Li, Jian Wang, Pengfei Zhang, Jinyan Shao, Junzhi Yu   +5 more
semanticscholar   +1 more source