Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 409-422 |
| Seitenumfang | 14 |
| Fachzeitschrift | International journal of control |
| Jahrgang | 90 |
| Ausgabenummer | 3 |
| Publikationsstatus | Veröffentlicht - 4 März 2017 |
Abstract
A growing number of researchers consider iterative learning control (ILC) a promising tool for numerous control problems in biomedical application systems. We will briefly discuss why classical ILC theory is technically too restrictive for some of these applications. Subsequently, we will extend the classical ILC design in the lifted systems framework to the class of repetitive trajectory tracking tasks with variable pass length. We will analyse the closed-loop dynamics for two standard learning laws, and we will discuss in which sense the tracking error can be reduced by which controller design strategies. Necessary and sufficient conditions for monotonic convergence will be derived. We then summarise all results in a set of practical controller design guidelines. Finally, a simulation study is presented, which demonstrates the usefulness of these guidelines and illustrates the special dynamics that occur in variable pass length learning.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Angewandte Informatik
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in: International journal of control, Jahrgang 90, Nr. 3, 04.03.2017, S. 409-422.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Monotonic convergence of iterative learning control systems with variable pass length
AU - Seel, Thomas
AU - Schauer, Thomas
AU - Raisch, Jörg
PY - 2017/3/4
Y1 - 2017/3/4
N2 - A growing number of researchers consider iterative learning control (ILC) a promising tool for numerous control problems in biomedical application systems. We will briefly discuss why classical ILC theory is technically too restrictive for some of these applications. Subsequently, we will extend the classical ILC design in the lifted systems framework to the class of repetitive trajectory tracking tasks with variable pass length. We will analyse the closed-loop dynamics for two standard learning laws, and we will discuss in which sense the tracking error can be reduced by which controller design strategies. Necessary and sufficient conditions for monotonic convergence will be derived. We then summarise all results in a set of practical controller design guidelines. Finally, a simulation study is presented, which demonstrates the usefulness of these guidelines and illustrates the special dynamics that occur in variable pass length learning.
AB - A growing number of researchers consider iterative learning control (ILC) a promising tool for numerous control problems in biomedical application systems. We will briefly discuss why classical ILC theory is technically too restrictive for some of these applications. Subsequently, we will extend the classical ILC design in the lifted systems framework to the class of repetitive trajectory tracking tasks with variable pass length. We will analyse the closed-loop dynamics for two standard learning laws, and we will discuss in which sense the tracking error can be reduced by which controller design strategies. Necessary and sufficient conditions for monotonic convergence will be derived. We then summarise all results in a set of practical controller design guidelines. Finally, a simulation study is presented, which demonstrates the usefulness of these guidelines and illustrates the special dynamics that occur in variable pass length learning.
KW - Iterative learning control
KW - biomedical applications
KW - lifted system framework
KW - monotonic convergence
KW - non-uniform trial duration
UR - http://www.scopus.com/inward/record.url?scp=84973122040&partnerID=8YFLogxK
U2 - 10.1080/00207179.2016.1183172
DO - 10.1080/00207179.2016.1183172
M3 - Article
VL - 90
SP - 409
EP - 422
JO - International journal of control
JF - International journal of control
SN - 0020-7179
IS - 3
ER -