haozhg / omlLinks
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
☆30Updated 2 years ago
Alternatives and similar repositories for oml
Users that are interested in oml are comparing it to the libraries listed below
Sorting:
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆46Updated 4 years ago
- Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)☆58Updated 3 months ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆76Updated last year
- Koopman Reduced-Order Nonlinear Identification and Control☆90Updated 5 years ago
- ☆87Updated 2 years ago
- Koopman operator identification library in Python, compatible with `scikit-learn`☆80Updated 2 months ago
- Code for the paper, "Industrial, large-scale model predictive control with structured neural networks."☆17Updated 3 years ago
- Reduced Order Model Predictive Control☆24Updated 3 years ago
- A Neural Network Approach for Real-Time High-Dimensional Optimal Control☆26Updated 2 years ago
- Differentiable predictive control (DPC) policy optimization examples.☆55Updated last year
- Adaptive control-oriented meta-learning for nonlinear systems☆64Updated 4 years ago
- "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga☆45Updated last year
- This repository contains the source code for “Unscented Kalman filter stochastic nonlinear model predictive control” (UKF-SNMPC).☆58Updated 2 years ago
- ☆39Updated last year
- Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…☆28Updated 2 years ago
- Model-based Control using Koopman Operators☆51Updated 5 years ago
- ☆45Updated 3 years ago
- Repository for Koopman based learning and nonlinear control☆45Updated 2 years ago
- Empowering extended Kalman filter (EKF) with Sparse Identification of Nonlinear Dynamics (SINDy)☆57Updated 2 months ago
- Data-driven Koopman control theory applied to reinforcement learning!☆33Updated last year
- Enforcing robust control guarantees within neural network policies☆54Updated 4 years ago
- This project deals with learning to reproduce the input-output behavior of state-space models using recurrent neural networks and the Ker…☆33Updated 3 months ago
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆96Updated 3 years ago
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆113Updated last year
- Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco …☆20Updated last year
- Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gy…☆141Updated 2 years ago
- Python code of the paper "Model structures and fitting criteria for system identification with neural networks" by Marco Forgione and Dar…☆21Updated 3 years ago
- Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach☆83Updated 6 years ago
- Toolbox for system identification of nonlinear state space grey-box models using CasADi☆26Updated last year
- A framework for neural network control of dynamical systems over graphs.☆57Updated 2 years ago