Output Regulation by Postprocessing Internal Models for a Class of Multivariable Nonlinear Systems
Abstract
In this paper we propose a new design paradigm, which employing a postprocessing internal model unit, to approach the problem of output regulation for a class of multivariable minimum-phase nonlinear systems possessing a partial normal form. Contrary to previous approaches, the proposed regulator handles control inputs of dimension larger than the number of regulated variables, provided that a controllability assumption holds, and can employ additional measurements that need not to vanish at the ideal error-zeroing steady state, but that can be useful for stabilization purposes or to fulfil the minimum-phase requirement. Conditions for practical and asymptotic output regulation are given, underlying how in postprocessing schemes the design of internal models is necessarily intertwined with that of the stabilizer.
Cite
@article{arxiv.2111.12678,
title = {Output Regulation by Postprocessing Internal Models for a Class of Multivariable Nonlinear Systems},
author = {Michelangelo Bin and Lorenzo Marconi},
journal= {arXiv preprint arXiv:2111.12678},
year = {2021}
}
Comments
The published version contains a few small rendering issues in some formulae. Here, these are corrected