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:
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆79Updated last year
- Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)☆62Updated 7 months ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆49Updated 5 years ago
- Control simulation of a mass-spring-damper system using a model-based reinforcement learning algorithm☆22Updated 4 years ago
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆129Updated 2 years ago
- ☆291Updated 5 years ago
- Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gy…☆144Updated 2 years ago
- A nonlinear MPC (NMPC) library for using a neural network as model.☆10Updated last year
- A Python package for linear subspace identification, nonlinear system identification, and nonlinear regression using Jax☆52Updated last month
- ☆77Updated 7 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆92Updated 5 years ago
- Python library that implements DeePC: Data-Enabled Predictive Control☆82Updated last year
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆32Updated 3 years ago
- HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problem…☆185Updated last week
- Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"☆24Updated 4 years ago
- Data-driven Koopman control theory applied to reinforcement learning!☆34Updated 2 years ago
- ☆42Updated 2 years ago
- Code for "SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning" by Zolman et al.☆142Updated 2 months ago
- A data-driven framework for control of nonlinear flows with Koopman Model Predictive Control☆155Updated 5 years ago
- System identification in PyTorch☆27Updated 2 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
- Master thesis spring 2019. Template to be futher used by the department of chemical engineering at NTNU,☆36Updated last year
- Soure code for Deep Koopman with Control☆94Updated 3 years ago
- A general-purpose Python package for Koopman theory using deep learning.☆115Updated last month
- Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach☆84Updated 6 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆52Updated 4 years ago
- Repository for Koopman based learning and nonlinear control☆49Updated 2 years ago
- A framework for neural network control of dynamical systems over graphs.☆56Updated 3 years ago
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆98Updated 3 years ago
- Koopman operator☆28Updated 5 years ago