PIσ - PIσ Continuous Iterative Learning Control for Nonlinear Systems with Arbitrary Relative Degree

Lorenzo Cenceschi*, Franco Angelini, Cosimo Della Santina*, Antonio Bicchi

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)


Online-Offline Iterative Learning Control provides an effective and robust solution to learn precise trajectory tracking when dealing with repetitive tasks. Yet, these algorithms were developed under the assumption that the relative degree between input and output is one. This prevents applications in many practically meaningful situations - e.g. mechanical systems control. To overcome this issue, this manuscript proposes a PIσ - PIσ algorithm fusing information from the whole visible dynamics. We provide sufficient convergence conditions when the controlled system has a generic constant relative degree, and it is possibly subject to measurement delay. The controller is validated on several simulation scenarios, including learning to swing-up a soft pendulum.
Original languageEnglish
Title of host publicationProceedings of the European Control Conference (ECC 2021)
ISBN (Electronic)978-9-4638-4236-5
ISBN (Print)978-1-6654-7945-5
Publication statusPublished - 2021
Event2021 European Control Conference (ECC) - Virtual , Netherlands
Duration: 29 Jun 20212 Jul 2021


Conference2021 European Control Conference (ECC)

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


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