MaartenSchoukens / deepSILinks
Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)
☆61Updated 6 months ago
Alternatives and similar repositories for deepSI
Users that are interested in deepSI are comparing it to the libraries listed below
Sorting:
- Differentiable predictive control (DPC) policy optimization examples.☆58Updated 2 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 year
- Toolbox for system identification of nonlinear state space grey-box models using CasADi☆26Updated 2 years ago
- ☆73Updated 7 years ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆78Updated last year
- "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga☆47Updated last year
- This repository contains the source code for "Stochastic data-driven model predictive control using Gaussian processes" (SDD-GP-MPC).☆65Updated 2 years ago
- This repository contains the source code for “Unscented Kalman filter stochastic nonlinear model predictive control” (UKF-SNMPC).☆59Updated 2 years ago
- A Python package for linear subspace identification, nonlinear system identification, and nonlinear regression using Jax☆48Updated last week
- ☆287Updated 5 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆91Updated 5 years ago
- Continuous-time system identification with neural networks☆27Updated 3 months ago
- Model-based Control using Koopman Operators☆52Updated 5 years ago
- Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"☆24Updated 4 years ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆48Updated 4 years ago
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆31Updated 2 years ago
- Python library that implements DeePC: Data-Enabled Predictive Control☆78Updated last year
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆122Updated last year
- Adaptive control-oriented meta-learning for nonlinear systems☆67Updated 4 years ago
- [L4DC 2025] Automatic hyperparameter tuning for DeePC. Built by Michael Cummins at the Automatic Control Laboratory, ETH Zurich.☆22Updated last month
- Accompanying repository for our work "On the relationship between data-enabled predictive control and subspace predictive control".☆23Updated 2 years ago
- Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco …☆22Updated last year
- Companion code for Closed-Loop Koopman Operator Approximation☆16Updated last year
- Repository for Koopman based learning and nonlinear control☆49Updated 2 years ago
- A data-driven framework for control of nonlinear flows with Koopman Model Predictive Control☆151Updated 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
- A nonlinear MPC (NMPC) library for using a neural network as model.☆10Updated last year
- ☆14Updated 8 months ago
- Gaussian Process Model Dynamic System Identification Toolbox for Matlab☆94Updated 8 years ago
- SIMBa☆12Updated 8 months ago