Robust Discrete-Time Iterative Learning Control for Nonlinear Systems With Varying Initial State Shifts.
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| Title: | Robust Discrete-Time Iterative Learning Control for Nonlinear Systems With Varying Initial State Shifts. |
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| Authors: | Deyuan Meng1 dymeng23@126.com, Yingmin Jia1,2 ymjia@buaa.edu.cn, Junping Du3 junpingdu@126.com, Shiying Yuan4 yuansy@hpu.edu.cn |
| Source: | IEEE Transactions on Automatic Control. Nov2009, Vol. 54 Issue 11, p2626-2631. 5p. 1 Graph. |
| Subjects: | Discrete-time systems, Nonlinear systems, Robust control, Mathematical analysis, Mathematics education |
| Abstract: | This note is concerned with the robust discrete-time iterative learning control (ILC) design for nonlinear systems with varying initial state shifts. A two-gain ILC law is considered using a 2-D analysis approach. Sufficient conditions are derived to guarantee both convergence of the learning process for fixed initial condition and boundedness of the tracking error for variable initial condition, It is shown that the error data with anticipation in time can well handle the varying initial state shifts in discrete-time ILC. [ABSTRACT FROM AUTHOR] |
| Copyright of IEEE Transactions on Automatic Control is the property of IEEE 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 |
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| Items | – Name: Title Label: Title Group: Ti Data: Robust Discrete-Time Iterative Learning Control for Nonlinear Systems With Varying Initial State Shifts. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Deyuan+Meng%22">Deyuan Meng</searchLink><relatesTo>1</relatesTo><i> dymeng23@126.com</i><br /><searchLink fieldCode="AR" term="%22Yingmin+Jia%22">Yingmin Jia</searchLink><relatesTo>1,2</relatesTo><i> ymjia@buaa.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Junping+Du%22">Junping Du</searchLink><relatesTo>3</relatesTo><i> junpingdu@126.com</i><br /><searchLink fieldCode="AR" term="%22Shiying+Yuan%22">Shiying Yuan</searchLink><relatesTo>4</relatesTo><i> yuansy@hpu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Automatic+Control%22">IEEE Transactions on Automatic Control</searchLink>. Nov2009, Vol. 54 Issue 11, p2626-2631. 5p. 1 Graph. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Discrete-time+systems%22">Discrete-time systems</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+systems%22">Nonlinear systems</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+control%22">Robust control</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+analysis%22">Mathematical analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematics+education%22">Mathematics education</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This note is concerned with the robust discrete-time iterative learning control (ILC) design for nonlinear systems with varying initial state shifts. A two-gain ILC law is considered using a 2-D analysis approach. Sufficient conditions are derived to guarantee both convergence of the learning process for fixed initial condition and boundedness of the tracking error for variable initial condition, It is shown that the error data with anticipation in time can well handle the varying initial state shifts in discrete-time ILC. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Automatic Control is the property of IEEE 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: 10.1109/TAC.2009.2031564 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 5 StartPage: 2626 Subjects: – SubjectFull: Discrete-time systems Type: general – SubjectFull: Nonlinear systems Type: general – SubjectFull: Robust control Type: general – SubjectFull: Mathematical analysis Type: general – SubjectFull: Mathematics education Type: general Titles: – TitleFull: Robust Discrete-Time Iterative Learning Control for Nonlinear Systems With Varying Initial State Shifts. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Deyuan Meng – PersonEntity: Name: NameFull: Yingmin Jia – PersonEntity: Name: NameFull: Junping Du – PersonEntity: Name: NameFull: Shiying Yuan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 00189286 Numbering: – Type: volume Value: 54 – Type: issue Value: 11 Titles: – TitleFull: IEEE Transactions on Automatic Control Type: main |
| ResultId | 1 |
