MaartenSchoukens / deepSI
Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)
☆48Updated this week
Alternatives and similar repositories for deepSI:
Users that are interested in deepSI are comparing it to the libraries listed below
- Toolbox for system identification of nonlinear state space grey-box models using CasADi☆23Updated last year
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆30Updated 2 years ago
- This repository contains the source code for “Unscented Kalman filter stochastic nonlinear model predictive control” (UKF-SNMPC).☆59Updated last year
- "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga☆43Updated 7 months ago
- HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problem…☆170Updated last year
- ☆64Updated 6 years ago
- Codes accompanying the paper "Deep learning with transfer functions: new applications in system identification"☆20Updated last year
- Differentiable predictive control (DPC) policy optimization examples.☆50Updated last year
- Adaptive control-oriented meta-learning for nonlinear systems☆59Updated 3 years ago
- Continuous-time system identification with neural networks☆24Updated 3 years ago
- This repository contains the source code for "Stochastic data-driven model predictive control using Gaussian processes" (SDD-GP-MPC).☆50Updated last year
- Empowering extended Kalman filter (EKF) with Sparse Identification of Nonlinear Dynamics (SINDy)☆45Updated this week
- Python code of the paper "Efficient Calibration of Embedded MPC" (2020 IFAC World Congress) by Marco Forgione, Dario Piga, and Alberto Be…☆24Updated 3 years ago
- A Python package for linear subspace identification, nonlinear system identification, and nonlinear regression using Jax☆24Updated 2 weeks ago
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆91Updated last year
- Neural Networks with CasADi☆8Updated last week
- ☆41Updated 3 years ago
- Data Driven Reachability Analysis from Noisy Data☆23Updated 9 months ago
- Repository for Koopman based learning and nonlinear control☆38Updated 2 years ago
- Economic tuning of tracking (N)MPC problems.☆31Updated 2 years ago
- Koopman Reduced-Order Nonlinear Identification and Control☆85Updated 4 years ago
- Code for the paper, "Industrial, large-scale model predictive control with structured neural networks."☆17Updated 3 years ago
- AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.☆63Updated 8 months ago
- Automatic Tuning for Data-driven Model Predictive Control☆60Updated last year
- Codebase associated with paper "Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control"☆22Updated 4 years ago
- Model-based Control using Koopman Operators☆50Updated 4 years ago
- A multipurpose, easy-to-use Model Predictive Control design and simulation code☆16Updated 4 months ago
- Examples shown in class and recitation from AA203: Optimal and Learning-Based Control.☆48Updated 8 months ago
- Python library that implements DeePC: Data-Enabled Predictive Control☆64Updated 3 months ago
- ☆23Updated 3 years ago