Abstract
Iterative learning control (ILC) yields substantial performance improvement for repetitive motion tasks. While task-flexibility for non-repetitive motion tasks can be achieved with the use of basis functions, this typically comes with a trade-off in performance or design parameters. This study aims to achieve both task-flexibility and high performance with a single time-domain optimization framework. By defining a criterion combining the cost for performance and task-flexibility, an optimal feedforward with task-flexibility of basis function ILC and high performance surpassing standard norm-optimal ILC is obtained. Numerical validation on a two-mass motion system confirm the capabilities of the developed framework.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the European Control Conference, ECC 2024 |
| Publisher | IEEE |
| Pages | 1190-1195 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-3-9071-4410-7 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 2024 European Control Conference, ECC 2024 - Stockholm, Sweden Duration: 25 Jun 2024 → 28 Jun 2024 |
Conference
| Conference | 2024 European Control Conference, ECC 2024 |
|---|---|
| Country/Territory | Sweden |
| City | Stockholm |
| Period | 25/06/24 → 28/06/24 |
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-careOtherwise 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.