Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data

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

Short intro to scientific machine learning using physics informed neuronal networks. I used PyTorch as a framework.

MATLAB files for discovery of Poincaré maps

Code for discovering slow timescale dynamics using the SINDy method

Using data driven numerical methods to perform system identification, model reduction, and design controllers.

This repository focuses on the reconstruction of the Lorenz system, a well-known chaotic dynamical system, using the Sparse Identification of Nonlinear Dynamical systems (SINDy) algorithm. It aims to identify the governing equations of chaotic systems from data.

Code associated to the paper "Data-driven stabilization of periodic orbits"

Code for my BSc thesis about SINDy at Bocconi University