pnnl / deps_arXiv2020Links
Differentiable predictive control (DPC) policy optimization examples.
☆55Updated last year
Alternatives and similar repositories for deps_arXiv2020
Users that are interested in deps_arXiv2020 are comparing it to the libraries listed below
Sorting:
- Model-based Control using Koopman Operators☆51Updated 5 years ago
- Automatic Tuning for Data-driven Model Predictive Control☆67Updated 2 years ago
- Enforcing robust control guarantees within neural network policies☆54Updated 4 years ago
- Adaptive control-oriented meta-learning for nonlinear systems☆64Updated 4 years ago
- Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)☆58Updated 3 months ago
- Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"☆24Updated 4 years ago
- Companion code for Closed-Loop Koopman Operator Approximation☆16Updated last year
- This repository contains the source code for “Unscented Kalman filter stochastic nonlinear model predictive control” (UKF-SNMPC).☆58Updated 2 years ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆46Updated 4 years ago
- Repository for Koopman based learning and nonlinear control☆45Updated 2 years ago
- Toolbox for system identification of nonlinear state space grey-box models using CasADi☆26Updated last year
- This repository contains the source code for "Stochastic data-driven model predictive control using Gaussian processes" (SDD-GP-MPC).☆58Updated 2 years ago
- Data Driven Reachability Analysis from Noisy Data☆29Updated last year
- ☆24Updated 4 years ago
- ☆72Updated 7 years ago
- Code to reproduce examples in 'Closed-loop data-enabled predictive control' submitted to CDC 2020☆21Updated 5 years ago
- Continuous-time system identification with neural networks☆25Updated this week
- Pytorch implementation of Model Predictive Control with learned models☆30Updated 4 years ago
- Python code for implementing a set of basic robust model predictive control (RMPC) algorithms for linear systems.☆26Updated 3 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆90Updated 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…☆25Updated 4 years ago
- [L4DC 2025] Automatic hyperparameter tuning for DeePC. Built by Michael Cummins at the Automatic Control Laboratory, ETH Zurich.☆21Updated 7 months ago
- Material for the tutorial on "Physics-Informed Machine Learning (PIML) for Modeling and Control of Dynamical Systems" presented at the Am…☆19Updated last year
- A PyTorch implementation of MPC as a Function Approximator☆18Updated 3 years ago
- Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…☆28Updated 2 years ago
- Neural Koopman Lyapunov Control☆25Updated 2 years ago
- Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach☆83Updated 6 years ago
- "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga☆45Updated last year
- HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problem…☆181Updated last year
- ☆16Updated 3 years ago