AleksandarHaber / Machine-Learning-of-Dynamical-Systems-using-Recurrent-Neural-Networks
This project deals with learning to reproduce the input-output behavior of state-space models using recurrent neural networks and the Keras machine learning toolbox.
☆27Updated 2 months ago
Related projects ⓘ
Alternatives and complementary repositories for Machine-Learning-of-Dynamical-Systems-using-Recurrent-Neural-Networks
- AleksandarHaber / Subspace-Identification-State-Space-System-Identification-of-Dynamical-Systems-and-Time-Series-☆38Updated 8 months ago
- Koopman Reduced-Order Nonlinear Identification and Control☆83Updated 4 years ago
- Repository for construction of Koopman eigenfunctions for unknown dynamical systems and identification of a lifted state-space model usin…☆27Updated last year
- AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control☆29Updated 2 years ago
- "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga☆42Updated 5 months ago
- This repository contains the source code for “Unscented Kalman filter stochastic nonlinear model predictive control” (UKF-SNMPC).☆59Updated last year
- ☆41Updated 3 years ago
- Gaussian Process Model Dynamic System Identification Toolbox for Matlab☆89Updated 7 years ago
- Empowering extended Kalman filter (EKF) with Sparse Identification of Nonlinear Dynamics (SINDy)☆43Updated this week
- Companion code for Closed-Loop Koopman Operator Approximation☆15Updated 8 months ago
- Control simulation of a mass-spring-damper system using a model-based reinforcement learning algorithm☆20Updated 3 years ago
- Dynamical System Identification using python incorporating numerous powerful deep learning methods. (deepSI = deep System Identification)☆45Updated 2 weeks ago
- We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-infor…☆84Updated last year
- Python simulation and hardware library for learning and control☆20Updated last year
- ☆20Updated 3 years ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆42Updated 4 years ago
- Differentiable predictive control (DPC) policy optimization examples.☆47Updated last year
- ☆15Updated 3 years ago
- Reduced Order Model Predictive Control☆18Updated 2 years ago
- Model-based Control using Koopman Operators☆47Updated 4 years ago
- ☆57Updated 6 years ago
- 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
- Python code of the paper "Model structures and fitting criteria for system identification with neural networks" by Marco Forgione and Dar…☆20Updated 3 years ago
- Repository for Koopman based learning and nonlinear control☆37Updated last year
- Continuous-time system identification with neural networks☆24Updated 3 years ago
- Pytorch implementation of Model Predictive Control with learned models☆28Updated 4 years ago
- Toolbox for system identification of nonlinear state space grey-box models using CasADi☆23Updated last year
- A pseudo-spectral collocation based multi-phase Optimal control problem solver☆54Updated 4 months ago
- A general-purpose Python package for Koopman theory using deep learning.☆84Updated last year