Object
Title: Iterative learning control for vacuum heat treatment process
Abstract:
Distributed parameter systems constitute an important class of modern industrial processes. However, in many practical applications the engineers still tend to adapt some classical control techniques developed for lumped systems totally neglecting the spatial dynamice of investigated process. In a view of increasing demands imposed on system accuracy and performance such conventional control algorithms simply become insufficient and there is a great necessity for novel identification and control methods taking into account both the temporal and spatial dynamics. ; This work reports a dedicated approach to control design for repetitive thermal process consisting of the extension of the existing feedback control scheme with intelligent data-driven component using the iterative learning control technique. Although this is a method which emerged in the context of time-invariant systems, it become adapted to more complex systems due to its flexibility and inherent robustness. The characterization of the resulting control scheme is discussed together with control design and implementation details. In order to compare the quality of the regulation, the approach is illustrated with simulation on the realistic model of wafer heating in industrial vacuum furnace.
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License CC BY 4.0:
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Biblioteka Uniwersytetu Zielonogórskiego
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Object collections:
- Digital Library of Zielona Góra > Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Digital Library of Zielona Góra > Repository > Types of work > Articles
Last modified:
Apr 21, 2023
In our library since:
Apr 21, 2023
Number of object content hits:
60
All available object's versions:
https://zbc.uz.zgora.pl/publication/81283
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| Edition name | Date |
|---|---|
| Iterative learning control for vacuum heat treatment process | Apr 21, 2023 |
