Neural Network Based Nonlinear Observers
Optimization and Control
2020-03-17 v1
Abstract
Nonlinear observers based on the well-known concept of minimum energy estimation are discussed. The approach relies on an output injection operator determined by a Hamilton-Jacobi-Bellman equation and is subsequently approximated by a neural network. A suitable optimization problem allowing to learn the network parameters is proposed and numerically investigated for linear and nonlinear oscillators.
Cite
@article{arxiv.2003.07269,
title = {Neural Network Based Nonlinear Observers},
author = {Tobias Breiten and Karl Kunisch},
journal= {arXiv preprint arXiv:2003.07269},
year = {2020}
}