Gaussian Process based Passivation of a Class of Nonlinear Systems with Unknown Dynamics
Systems and Control
2018-11-19 v1
Abstract
The paper addresses the problem of passivation of a class of nonlinear systems where the dynamics are unknown. For this purpose, we use the highly flexible, data-driven Gaussian process regression for the identification of the unknown dynamics for feed-forward compensation. The closed loop system of the nonlinear system, the Gaussian process model and a feedback control law is guaranteed to be semi-passive with a specific probability. The predicted variance of the Gaussian process regression is used to bound the model error which additionally allows to specify the state space region where the closed-loop system behaves passive. Finally, the theoretical results are illustrated by a simulation.
Cite
@article{arxiv.1811.06648,
title = {Gaussian Process based Passivation of a Class of Nonlinear Systems with Unknown Dynamics},
author = {Thomas Beckers and Sandra Hirche},
journal= {arXiv preprint arXiv:1811.06648},
year = {2018}
}
Comments
Please cite the conference paper