forgi86 / sysid-neural-estimatorLinks
Code accompanying the paper "Learning neural state-space models: do we need a state estimator?"
☆10Updated 2 years ago
Alternatives and similar repositories for sysid-neural-estimator
Users that are interested in sysid-neural-estimator are comparing it to the libraries listed below
Sorting:
- Control simulation of a mass-spring-damper system using a model-based reinforcement learning algorithm☆22Updated 4 years ago
- Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)☆63Updated 8 months ago
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆131Updated 2 years ago
- Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gy…☆145Updated 2 years ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆81Updated last year
- ☆294Updated 5 years ago
- A nonlinear MPC (NMPC) library for using a neural network as model.☆10Updated last year
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆50Updated 5 years ago
- ☆78Updated 7 years ago
- A Python package for linear subspace identification, nonlinear system identification, and nonlinear regression using Jax☆52Updated 2 months ago
- Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…☆29Updated 3 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆92Updated 5 years ago
- Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"☆24Updated 5 years ago
- A data-driven framework for control of nonlinear flows with Koopman Model Predictive Control☆156Updated 5 years ago
- AleksandarHaber / Subspace-Identification-State-Space-System-Identification-of-Dynamical-Systems-and-Time-Series-☆49Updated 8 months ago
- Python library that implements DeePC: Data-Enabled Predictive Control☆87Updated last year
- System identification in PyTorch☆27Updated 2 years ago
- Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach☆84Updated 6 years ago
- Code to reproduce the results of the paper In-context learning for model-free system identification☆18Updated last year
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆43Updated 6 years ago
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆99Updated 3 years ago
- Data-driven Koopman control theory applied to reinforcement learning!☆34Updated 2 years ago
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆33Updated 3 years ago
- HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problem…☆188Updated last month
- A framework for neural network control of dynamical systems over graphs.☆56Updated 3 years ago
- ☆42Updated 2 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆53Updated 4 years ago
- A package for computing data-driven approximations to the Koopman operator.☆395Updated last year
- Soure code for Deep Koopman with Control☆98Updated 3 years ago
- Koopman operator☆28Updated 5 years ago