Experimentally investigating the influence of changing payload stiffness on outer loop iterative learning control strategies with shaking table tests.
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| Title: | Experimentally investigating the influence of changing payload stiffness on outer loop iterative learning control strategies with shaking table tests. |
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| Authors: | Madabhushi, Srikanth SC1 (AUTHOR) mscs@colorado.edu, Hruby, Jaroslav2 (AUTHOR), Wham, Brad Parker1 (AUTHOR) |
| Source: | Journal of Vibration & Control. May2024, Vol. 30 Issue 9/10, p1933-1946. 14p. |
| Subjects: | Iterative learning control, Shaking table tests, Machine learning, Learning strategies, Industrial engineering, Adaptive control systems |
| Abstract: | Shaking tables are widely used across numerous engineering research and industrial sectors, including mechanical (e.g. automotive and aerospace testing), electrical (e.g. instrumentation testing) and civil (e.g. structural and geotechnical testing) engineering. It is commonly required to replicate the shake table motions accurately and precisely. Iterative learning control algorithms can be used to complement traditional proportional–integral–differential feedback control algorithms to optimize drive signals using a test payload prior to the real experiment. Historically, the design of these test payloads has focused on matching the mass of the actual payload and neglected its dynamic response. In this study, experimental results from shake table tests using multiple geotechnical containers with dry and saturated beds that exhibit a range of stiffnesses and material damping when shaken are presented. Errors between the demanded and achieved motions are explored and compared to the changing secant stiffness abstracted from the dynamic shear stress–strain loops of the payload. A clear trend emerges that demonstrates increased errors as the payload stiffness deviates from the constant stiffness test payload originally used with the open loop iterative learning control, and further the errors are not necessarily bounded by test payloads significantly softer or stiffer than the actual specimen. The findings support that in cases where repeatable, accurate and precise shake table motions are required for payloads that exhibit a complex material response that is not readily modelled mathematically, it may be necessary to reproduce the specimen's overall dynamic response during the iterative learning control process. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Vibration & Control is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 177167229 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Experimentally investigating the influence of changing payload stiffness on outer loop iterative learning control strategies with shaking table tests. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Madabhushi%2C+Srikanth+SC%22">Madabhushi, Srikanth SC</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mscs@colorado.edu</i><br /><searchLink fieldCode="AR" term="%22Hruby%2C+Jaroslav%22">Hruby, Jaroslav</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wham%2C+Brad+Parker%22">Wham, Brad Parker</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Vibration+%26+Control%22">Journal of Vibration & Control</searchLink>. May2024, Vol. 30 Issue 9/10, p1933-1946. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Iterative+learning+control%22">Iterative learning control</searchLink><br /><searchLink fieldCode="DE" term="%22Shaking+table+tests%22">Shaking table tests</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+strategies%22">Learning strategies</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+engineering%22">Industrial engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+control+systems%22">Adaptive control systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Shaking tables are widely used across numerous engineering research and industrial sectors, including mechanical (e.g. automotive and aerospace testing), electrical (e.g. instrumentation testing) and civil (e.g. structural and geotechnical testing) engineering. It is commonly required to replicate the shake table motions accurately and precisely. Iterative learning control algorithms can be used to complement traditional proportional–integral–differential feedback control algorithms to optimize drive signals using a test payload prior to the real experiment. Historically, the design of these test payloads has focused on matching the mass of the actual payload and neglected its dynamic response. In this study, experimental results from shake table tests using multiple geotechnical containers with dry and saturated beds that exhibit a range of stiffnesses and material damping when shaken are presented. Errors between the demanded and achieved motions are explored and compared to the changing secant stiffness abstracted from the dynamic shear stress–strain loops of the payload. A clear trend emerges that demonstrates increased errors as the payload stiffness deviates from the constant stiffness test payload originally used with the open loop iterative learning control, and further the errors are not necessarily bounded by test payloads significantly softer or stiffer than the actual specimen. The findings support that in cases where repeatable, accurate and precise shake table motions are required for payloads that exhibit a complex material response that is not readily modelled mathematically, it may be necessary to reproduce the specimen's overall dynamic response during the iterative learning control process. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Vibration & Control is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1177/10775463231173018 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1933 Subjects: – SubjectFull: Iterative learning control Type: general – SubjectFull: Shaking table tests Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Learning strategies Type: general – SubjectFull: Industrial engineering Type: general – SubjectFull: Adaptive control systems Type: general Titles: – TitleFull: Experimentally investigating the influence of changing payload stiffness on outer loop iterative learning control strategies with shaking table tests. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Madabhushi, Srikanth SC – PersonEntity: Name: NameFull: Hruby, Jaroslav – PersonEntity: Name: NameFull: Wham, Brad Parker IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 10775463 Numbering: – Type: volume Value: 30 – Type: issue Value: 9/10 Titles: – TitleFull: Journal of Vibration & Control Type: main |
| ResultId | 1 |
