Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

Extended Dynamic Mode Decomposition for system identification from time series data (with dictionary learning, control and streaming options). Diffusion Maps to extract geometric description from data.

This repository contains all the work developed in the context of the Master Thesis dissertation entitled Model Predictive Control for Wake Steering: a Koopman Dynamic Mode Decomposition Approach. The repository includes all developed documentation (dissertation, extended abstract, poster and presentation) source code (MATLAB script and function…

My Master Thesis in the area of Data-Driven Control Engineering

This code can be used to reproduce the results in our paper ``Linearizing uncertainties that matter for control: the Koopman operator in the dual control context''.

koopman operator examples

A framework for data-driven modeling and analysis of granular materials in the strongly nonlinear regime using the modern Koopman theory