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Essential and Redundant Internal Models in Nonlinear Output Regulation

Authors: Lorenzo Marconi, Laurent Praly, in Analysis and Design of Nonlinear Control Systems, Alessandro Astolfi, Lorenzo Marconi eds., Springer Verlag, 2008 DOI: 10.1007/978-3-540-74358-3_16
This paper is focused on the problem of output regulation for nonlinear systems within the main framework developed in [23]. The main goal is to complement that theory with some new results showing how the dimension of the internal model-based regulator can be reduced by preserving the so-called internal model property. It is shown how the problem of reducing the regulator dimension can be approached by identifying “observability” parts of the so-called steady-state input generator system. A local analysis based on canonical geometric tools and local observability decomposition is also presented to identify lower bounds on the regulator dimension. Possible benefits in designing redundant internal models are also discussed.
BibTeX:
@Incollection{,
author = {Lorenzo Marconi, Laurent Praly},
title = {Essential and Redundant Internal Models in Nonlinear Output Regulation},
booktitle = {Analysis and Design of Nonlinear Control Systems},
editor = {Alessandro Astolfi, Lorenzo Marconi},
publisher = {Springer Verlag},
address = {},
pages = {263-283},
year = {2008},
abstract = {This paper is focused on the problem of output regulation for nonlinear systems within the main framework developed in [23]. The main goal is to complement that theory with some new results showing how the dimension of the internal model-based regulator can be reduced by preserving the so-called internal model property. It is shown how the problem of reducing the regulator dimension can be approached by identifying “observability” parts of the so-called steady-state input generator system. A local analysis based on canonical geometric tools and local observability decomposition is also presented to identify lower bounds on the regulator dimension. Possible benefits in designing redundant internal models are also discussed.},
keywords = {}}
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