rssalessio / PyDeePC
Python library that implements DeePC: Data-Enabled Predictive Control
☆65Updated 4 months ago
Alternatives and similar repositories for PyDeePC:
Users that are interested in PyDeePC are comparing it to the libraries listed below
- This repository contains the source code for "Stochastic data-driven model predictive control using Gaussian processes" (SDD-GP-MPC).☆50Updated last year
- J. Berberich, J. Köhler, M. A. Müller and F. Allgöwer, "Data-Driven Model Predictive Control With Stability and Robustness Guarantees," i…☆41Updated last year
- Data-enabled predictive control (DeePC) implementation using MATLAB☆22Updated last year
- Data-Driven Predictive Control☆63Updated 11 months ago
- ☆65Updated 6 years ago
- Accompanying repository for our work "On the relationship between data-enabled predictive control and subspace predictive control".☆22Updated 2 years ago
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆94Updated last year
- ☆12Updated last year
- Python code for implementing a set of basic robust model predictive control (RMPC) algorithms for linear systems.☆25Updated 2 years ago
- Codebase for generating linear/bilinear/nonlinear Koopman model realizations from data and constructing MPC controllers.☆19Updated 3 years ago
- ☆14Updated 4 years ago
- This is a Python realization for Milan Korda and Igor Mezic's paper Linear predictors for nonlinear dynamical systems: Koopman operator m…☆10Updated last year
- Code to reproduce examples in 'Closed-loop data-enabled predictive control' submitted to CDC 2020☆20Updated 4 years ago
- A wrapped package for Data-enabled predictive control (DeePC) implementation. Including DeePC and Robust DeePC design with multiple objec…☆17Updated 2 months ago
- A data-driven framework for control of nonlinear flows with Koopman Model Predictive Control☆130Updated 4 years ago
- Develop a Koopman operator based MPC for controlling a quadrotor☆48Updated 4 months ago
- Supplemental code for "Data-driven Control of Soft Robots Using Koopman Operator Theory," by Daniel Bruder, Xun Fu, R. Brent Gillespie, C…☆65Updated 4 years ago
- code of paper "Robust and kernelized data-enabled predictive control for nonlinear systems"☆13Updated last year
- Automatic hyperparameter tuning for DeePC. Built by Michael Cummins at the Automatic Control Laboratory, ETH Zurich.☆14Updated 2 months ago
- a repository of the codes related with the paper published in the journal paper (check the readme file).☆19Updated 4 years ago
- Soure code for Deep Koopman with Control☆69Updated 2 years ago
- Supplemental code for "Auto-Generation of Mission-Oriented Robot Controllers Using Bayesian-Based Koopman Operator"☆13Updated last year
- ☆17Updated 4 years ago
- Koopman operator☆27Updated 5 years ago
- Python code of the paper "Efficient Calibration of Embedded MPC" (2020 IFAC World Congress) by Marco Forgione, Dario Piga, and Alberto Be…☆24Updated 3 years ago
- Repository for Koopman based learning and nonlinear control☆38Updated 2 years ago
- The code accompanies the publication "Feedback Linearization based on Gaussian Processes with event-triggered Online Learning" by Jonas U…☆42Updated 3 years ago
- ☆11Updated last year
- Model-based Control using Koopman Operators☆51Updated 4 years ago
- Learning-Based Model Predictive Control (LBMPC)☆97Updated 5 years ago