Python library that implements DeePC: Data-Enabled Predictive Control
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Updated
Oct 17, 2022 - Python
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.
Virtual Reference Feedback Tuning (VRFT) Python Library - Alessio Russo ([email protected])
Python library that implements ZPC: Zonotopic Data-Driven Predictive Control.
Automatic hyperparameter tuning for DeePC. Built by Michael Cummins at the Automotaic Control Laboratory, ETH Zurich.
Code for the paper Analysis and Detectability of Offline Data Poisoning Attacks on Linear Systems.
A wrapped package for Data-enabled predictive control (DeePC) implementation. Including DeePC and Robust DeePC design with multiple objective functions.
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.
Tube-Based Zonotopic Data Driven Predictive Control
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.
Particle Gibbs-based optimal control with performance guarantees for unknown systems with latent states
Code for my project on 'Neural system identification and control for Formula Student Driverless cars'
Data-driven control examples
Code for journal publication 10.1109/OJCSYS.2023.3291596
Virtual Reference Feedback Tuning (VRFT) python library forked from Alessio Russo.
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