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AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
Model-based Control using Koopman Operators
a little library to help me with things involving Koopman operators
This repository contains the code for bilinear models for serial manipulators and the corresponding ZNN controller described in paper titled "Real-Time Constrained Tracking Control of Redundant Manipulators Using a Koopman-Zeroing Neural Network Framework".
In this work, we present a novel approach that combines the power of Koopman operators and deep neural networks to generate a linear representation of the Duffing oscillator. This approach enables effective parameter estimation and accurate prediction of the oscillator's future behavior.
A repo for using different dynamic world modeling for prediction and control: including deep learning based koopman and State-Space Modes (SSM)
project for my essay on how to use neural networks to linearise nonlinear dynamical systems
Library for the analysis of time-evolving graphs
Code for running the analyses from the article "Propofol destabilizies neural dynamics across cortex"
koopman operator examples
A repository for an Generalized Momenta based Koopman algorithm described for the paper titled "Generalized Momenta-Based Koopman Formalism for Robust Control of Euler-Lagrangian Systems".
For research into the application of Koopman operators at Boston University.
This repository is a supplementary documentation for the Multi-Model Parameterized Koopman (MMPK) framework capturing results through software and hardware deployments
Transfer operator toolbox for numpy/torch.
🏎️ Model and simulate vehicle suspension dynamics using Python and Laplace Transforms for accurate analysis of second-order LTI systems.
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