There are 13 repositories under system-identification topic.
A package for the sparse identification of nonlinear dynamical systems from data
A Python Package For System Identification Using NARMAX Models
PDE-Net: Learning PDEs from Data
Control adaptive filters with neural networks.
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
System Identification toolbox, compatible with ControlSystems.jl
State estimation, smoothing and parameter estimation using Kalman and particle filters.
Embedded Firmware Control Systems Toolbox (Pure C and GNU Octave)
A MATLAB package for modelling multivariate stimulus-response data
AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
Subspace methods for MIMO system identification
SLICOT - A Fortran subroutines library for systems and control
The usage of MATLAB System Identification Toolbox and PID parameters adjustment
A fully-featured flight simulator, capable of real-time lifting-line aerodynamic modelling.
My collection of implementations of adaptive filters.
Vibration Testing module affiliated with the in-progress manuscript Vibration Testing with Modal Analysis and Health Monitoring- Python version
AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)
Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurements".
All in one control interface for quadrotors in ROS.
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"
Continuous-time system identification with neural networks
Control in C++
A set of Matlab/Octave files that performs a method of Nonlinear System Identification.
An open-source linear control toolbox for MATLAB.
Codes accompanying the paper "Deep learning with transfer functions: new applications in system identification"
Python code of the paper "Model structures and fitting criteria for system identification with neural networks" by Marco Forgione and Dario Piga.
SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations
Source for my 2012 UCD dissertation "Human Control of a Bicycle"