This note describes a reference governor design for a continuous-time nonlinear system with an additive disturbance. The design is based on predicting the response of the nonlinear system by the response of a linear model with a set-bounded prediction error, where a state-and-input dependent bound on the prediction error is explicitly characterized using logarithmic norms. The online optimization is reduced to a convex quadratic program with linear inequality constraints. Two numerical examples are reported.
@article{arxiv.1908.09460,
title = {A Reference Governor for Nonlinear Systems with Disturbance Inputs Based on Logarithmic Norms and Quadratic Programming},
author = {Nan Li and Ilya Kolmanovsky and Anouck Girard},
journal= {arXiv preprint arXiv:1908.09460},
year = {2019}
}