Practical asymptotic stability of data-driven model predictive control using extended DMD
The extended Dynamic Mode Decomposition (eDMD) is a very popular method to obtain
data-driven surrogate models for nonlinear (control) systems governed by ordinary and …
data-driven surrogate models for nonlinear (control) systems governed by ordinary and …
Computationally efficient data-driven discovery and linear representation of nonlinear systems for control
M Tiwari, G Nehma, B Lusch - IEEE Control Systems Letters, 2023 - ieeexplore.ieee.org
This letter focuses on developing a data-driven framework using Koopman operator theory
for system identification and linearization of nonlinear systems for control. Our proposed …
for system identification and linearization of nonlinear systems for control. Our proposed …
Extracting Koopman operators for prediction and control of non-linear dynamics using two-stage learning and oblique projections
D Uchida, K Duraisamy - arXiv preprint arXiv:2308.13051, 2023 - arxiv.org
The Koopman operator framework provides a perspective that non-linear dynamics can be
described through the lens of linear operators acting on function spaces. As the framework …
described through the lens of linear operators acting on function spaces. As the framework …
Stackelberg game-theoretic trajectory guidance for multi-robot systems with koopman operator
Guided trajectory planning involves a leader robotic agent strategically directing a follower
robotic agent to collaboratively reach a designated destination. However, this task becomes …
robotic agent to collaboratively reach a designated destination. However, this task becomes …
Leveraging KANs For Enhanced Deep Koopman Operator Discovery
G Nehma, M Tiwari - arXiv preprint arXiv:2406.02875, 2024 - arxiv.org
Multi-layer perceptrons (MLP's) have been extensively utilized in discovering Deep
Koopman operators for linearizing nonlinear dynamics. With the emergence of Kolmogorov …
Koopman operators for linearizing nonlinear dynamics. With the emergence of Kolmogorov …
Koopman Operator Theory and Dynamic Mode Decomposition in Data-Driven Science and Engineering A Comprehensive Review
Poincaré's geometric representation has long been fundamental in dynamical system
analysis. However, its limitations in handling high-dimensional and uncertain systems have …
analysis. However, its limitations in handling high-dimensional and uncertain systems have …
Convolution and Autoencoders Applied to Nonlinear Differential Equations
N Borquaye - 2023 - dc.etsu.edu
Autoencoders, a type of artificial neural network, have gained recognition by researchers in
various fields, especially machine learning due to their vast applications in data …
various fields, especially machine learning due to their vast applications in data …