IEEE Transactions on Automatic Control, Vol.65, No.7, 3207-3214, 2020
A Reference Governor for Nonlinear Systems With Disturbance Inputs Based on Logarithmic Norms and Quadratic Programming
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.
Keywords:Nonlinear systems;Predictive models;Steady-state;Computational modeling;Quadratic programming;Additives;Nonlinear systems;quadratic programming;reference governors (RG);state and control constraints