Controllability Aspects for Iterative Learning Control
(English)Manuscript (preprint) (Other academic)
This paper discusses the aspects of controllability in the iteration domain for systems that are controlled using iterative learning control (ILC). The focus is on controllability for a proposed state space model in the iteration domain and it relates to an assumption often used to prove convergence of ILC algorithms. It is shown that instead of investigating controllability it is more suitable to use the concept of target path controllability (TPC), where it is investigated if a system can follow a trajectory instead of the ability to control the system to an arbitrary point in the state space. Finally, a simulation study is performed to show how the ILC algorithm can be designed using the LQ-method, if the state space model in the iteration domain is output controllable. The LQ-method is compared to the standard norm-optimal ILC algorithm, where it is shown that the control error can be reduced significantly using the LQ-method compared to the norm-optimal approach.
Iterative Learning Control, Controllability, Output controllability, Target path controllability
IdentifiersURN: urn:nbn:se:liu:diva-105342OAI: oai:DiVA.org:liu-105342DiVA: diva2:705989
ProjectsVinnova Excellence Center LINK-SICExcellence Center at Linköping-Lund in Information Technology, ELLIIT
FunderVinnovaeLLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications