A dual geometric test for forward-flatness

Forward-flatness is a generalization of static feedback linearizability and a special case of a more general flatness concept for discrete-time systems. Recently, it has been shown that this practically quite relevant property can be checked by computing a unique sequence of involutive distributions which generalizes the well-known static feedback linearization test. In this paper, a dual test for forward-flatness based on a unique sequence of integrable codistributions is derived. Since the main mathematical operations for determining this sequence are the intersection of codistributions and the calculation of Lie derivatives of 1-forms, it is computationally quite efficient. Furthermore, the formulation with codistributions also facilitates a comparison with the existing discrete-time literature regarding the closely related topic of dynamic feedback linearization, which is mostly formulated in terms of 1-forms rather than vector fields. The presented results are illustrated by two examples.

Authors

Publication Details

Journal
Automatica
Published
2025-06-17
DOI
https://doi.org/10.1016/j.automatica.2025.112425
Citations
1
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
1.21

Funders

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article

A dual geometric test for forward-flatness

Bernd Kolar, Markus Schöberl, Johannes Schrotshamer
1 citations
Automatica
Robotic Mechanisms and Dynamics
1.21
article

A dual geometric test for forward-flatness

Bernd Kolar, Markus Schöberl, Johannes Schrotshamer
article en
1 citations

Abstract

Forward-flatness is a generalization of static feedback linearizability and a special case of a more general flatness concept for discrete-time systems. Recently, it has been shown that this practically quite relevant property can be checked by computing a unique sequence of involutive distributions which generalizes the well-known static feedback linearization test. In this paper, a dual test for forward-flatness based on a unique sequence of integrable codistributions is derived. Since the main mathematical operations for determining this sequence are the intersection of codistributions and the calculation of Lie derivatives of 1-forms, it is computationally quite efficient. Furthermore, the formulation with codistributions also facilitates a comparison with the existing discrete-time literature regarding the closely related topic of dynamic feedback linearization, which is mostly formulated in terms of 1-forms rather than vector fields. The presented results are illustrated by two examples.

AutomaticaVol. 179
Austrian Science Fund
Climate action
Openalex Percentile: Top 20%
Robotic Mechanisms and Dynamics
1.21
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