A receding-horizon regulator for nonlinear systems and a neural approximation

@article{Parisini1995ARR,
title={A receding-horizon regulator for nonlinear systems and a neural approximation},
author={Thomas Parisini and Riccardo Zoppoli},
journal={Automatica},
year={1995},
volume={31},
pages={1443-1451}
}

Abstiaet-A receding-horizon (RH) optimal control scheme for a discrete-time nonlinear dynamic system is presented. A nonquadratic cost function is considered, and constraints are imposed on both the state and control vectors. Two main contributions are reported. The first consists in deriving a stabilizing regulator by adding a proper terminal penalty function to the process cost. The control vector is generated by means of a feedback control law computed off line instead of computing it on… CONTINUE READING