System Identification for Hybrid Systems using Neural Networks

Mattias Fält, Pontus Giselsson

Published 2019-11-28Version 1

With new advances in machine learning and in particular powerful learning libraries, we illustrate some of the new possibilities they enable in terms of nonlinear system identification. For a large class of hybrid systems, we explain how these tools allow for identification of complex dynamics using neural networks. We illustrate the method by examining the performance on a quad-rotor example.