A package for the sparse identification of nonlinear dynamical systems from data

A Python Package For System Identification Using NARMAX Models

Control adaptive filters with neural networks.

A framework for gene expression programming (an evolutionary algorithm) in Python

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.

AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.

A fully-featured flight simulator, capable of real-time lifting-line aerodynamic modelling.

My collection of implementations of adaptive filters.

AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)

AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control

Continuous-time system identification with neural networks

System identification in PyTorch

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

Rex is a JAX-powered framework for sim-to-real robotics.

An optimized LMS algorithm

Companion code for Closed-Loop Koopman Operator Approximation

System identification toolkit for multistep prediction using deep learning and hybrid methods.