Object
Title: Repetitive Process Based Higher-order Iterative Learning Control Law Design
Creator:
Maniarski, Robert ; Paszke, Wojciech (1975- ) ; Chu, Bing ; Rogers, Eric
Date:
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Abstract:
This paper uses the repetitive process setting to develop new results on the design ofhigher-order ILC control laws. The basic idea of higher-order ILC is to use information froma finite number of previous trials, as opposed to just the last trial, to update the controlinput to be applied on the next trial, with the primary objective of improving the errorconvergence performance. ; The sufficient conditions ensuring the convergence of the resultingcontrol scheme are established with repetitive process setting and through utilizing non-unitmemory repetitive process models. Also, the corresponding control law gains are derivedfrom a set of linear matrix inequality constraints. Finally, a practical example is used todemonstrate the properties of the new design.
Description:
artykuł zamieszczony w materiałach konferencyjnych "62nd IEEE Conference on Decision and Control"
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License CC BY 4.0:
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Biblioteka Uniwersytetu Zielonogórskiego
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Object collections:
- Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Repository > Types of work > Articles
Last modified:
Feb 13, 2024
In our library since:
Apr 21, 2023
Number of object content hits:
164
All available object's versions:
https://zbc.uz.zgora.pl/repozytorium/publication/81281
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| Edition name | Date |
|---|---|
| Repetitive Process Based Higher-order Iterative Learning Control Law Design | Feb 13, 2024 |
