System Identification for Hybrid Systems using Neural Networks
Optimization and Control
2019-12-02 v1
Abstract
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.
Cite
@article{arxiv.1911.12663,
title = {System Identification for Hybrid Systems using Neural Networks},
author = {Mattias Fält and Pontus Giselsson},
journal= {arXiv preprint arXiv:1911.12663},
year = {2019}
}