Python library that implements DeePC: Data-Enabled Predictive Control

J. Berberich, J. Köhler, M. A. Müller and F. Allgöwer, "Data-Driven Model Predictive Control With Stability and Robustness Guarantees," in IEEE Transactions on Automatic Control, vol. 66, no. 4, pp. 1702-1717, April 2021, doi: 10.1109/TAC.2020.3000182.

A wrapped package for Data-enabled predictive control (DeePC) implementation. Including DeePC and Robust DeePC design with multiple objective functions.

[L4DC 2025] Automatic hyperparameter tuning for DeePC. Built by Michael Cummins at the Automatic Control Laboratory, ETH Zurich.

This project is source code of paper Deep DeePC: Data-enabled predictive control with low or no online optimization using deep learning by X. Zhang, K. Zhang, Z. Li, and X. Yin. The objective of this work is to learn the DeePC operator using a neural network and bypass online optimization of conventional DeePC for efficient online implementation.

Z. Sun, Q. Wang, J. Pan and Y. Xia, "Data-Driven MPC for Linear Systems using Reinforcement Learning," 2021 China Automation Congress (CAC), Beijing, China, 2021, pp. 394-399, doi: 10.1109/CAC53003.2021.9728233.

Virtual Reference Feedback Tuning (VRFT) Python Library - Alessio Russo (alessior@kth.se)

Robust and nonlinear Direct Data-Driven MPC controllers for LTI and nonlinear systems in Python

Python library that implements ZPC: Zonotopic Data-Driven Predictive Control.

Tube-Based Zonotopic Data Driven Predictive Control

Code for the paper Analysis and Detectability of Offline Data Poisoning Attacks on Linear Systems.

Particle Gibbs-based optimal control with performance guarantees for unknown systems with latent states

Code for journal publication 10.1109/OJCSYS.2023.3291596

Efficient Computation of Lyapunov Functions Using Deep Neural Networks for the Assessment of Stability in Controller Design

This is the Julia implementation of the behavioral control DeePC algorithm.

Koopman-based robust model predictive control for thermal management of a 2R2C building model

This repository contains supplementary material to the paper "Adaptive Koopman Model Predictive Control of Simple Serial Robots".

Python implementation of the adaptive Koopman model predictive control algorithm

Code for my project on 'Neural system identification and control for Formula Student Driverless cars'

Code for paper "Co-state Neural Network for Real-time Nonlinear Optimal Control with Input Constraints" at ACC 2025