Dynamic output-only iterative learning control design
Dynamic output-only iterative learning control design
Iterative learning control applies to systems that repeatedly execute the same finite duration task. The distinguishing feature of this form of control action is that all data generated on a previous execution of the task is available to compute the control action for the subsequent execution. This paper uses the repetitive process stability analysis and optimization techniques to design a dynamic controller that, in contrast to previous designs in the repetitive process/2D systems setting, does not require measurement of the state dynamics or observer-based estimation. Examples to demonstrate the application of the new design are given.
47072 - 147081
Hladowski, Lukasz
db41c3fd-6c9e-48e8-81e7-9613072c59b5
Galkowski, Krzysztof
322994ac-7e24-4350-ab72-cc80ac8078ef
Rogers, Eric
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Hladowski, Lukasz
db41c3fd-6c9e-48e8-81e7-9613072c59b5
Galkowski, Krzysztof
322994ac-7e24-4350-ab72-cc80ac8078ef
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
Hladowski, Lukasz, Galkowski, Krzysztof and Rogers, Eric
(2021)
Dynamic output-only iterative learning control design.
IEEE Access, .
(doi:10.1109/ACCESS.2021.3123868).
Abstract
Iterative learning control applies to systems that repeatedly execute the same finite duration task. The distinguishing feature of this form of control action is that all data generated on a previous execution of the task is available to compute the control action for the subsequent execution. This paper uses the repetitive process stability analysis and optimization techniques to design a dynamic controller that, in contrast to previous designs in the repetitive process/2D systems setting, does not require measurement of the state dynamics or observer-based estimation. Examples to demonstrate the application of the new design are given.
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e-pub ahead of print date: 27 October 2021
Identifiers
Local EPrints ID: 454884
URI: http://eprints.soton.ac.uk/id/eprint/454884
ISSN: 2169-3536
PURE UUID: 4946bdaf-ba90-41c6-987c-869d48877e61
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Date deposited: 01 Mar 2022 17:33
Last modified: 17 Mar 2024 02:37
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Author:
Lukasz Hladowski
Author:
Krzysztof Galkowski
Author:
Eric Rogers
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