Max E. Gilmore
Stability and convergence properties of forced infinite-dimensional discrete-time Lur'e systems
Gilmore, Max E.; Guiver, Chris; Logemann, Hartmut
Abstract
Incremental stability and convergence properties for forced, infinite-dimensional, discrete-time Lur'e systems are addressed. Lur'e systems have a linear and nonlinear component and arise as the feedback interconnection of a linear control system and a static nonlinearity. Discrete-time Lur'e systems arise in, for example, sampled-data control and integro-difference models. We provide conditions, reminiscent of classical absolute stability criteria, which are sufficient for a range of incremental stability properties and input-to-state stability (ISS). Consequences of our results include sufficient conditions for the converging-input converging-state (CICS) property, and convergence to periodic solutions under periodic forcing.
Citation
Gilmore, M. E., Guiver, C., & Logemann, H. (2020). Stability and convergence properties of forced infinite-dimensional discrete-time Lur'e systems. International Journal of Control, 93(12), 3026-3049. https://doi.org/10.1080/00207179.2019.1575528
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 23, 2019 |
Online Publication Date | Feb 22, 2019 |
Publication Date | 2020 |
Deposit Date | Jul 23, 2020 |
Publicly Available Date | Jul 23, 2020 |
Journal | International Journal of Control |
Print ISSN | 0020-7179 |
Electronic ISSN | 1366-5820 |
Publisher | Taylor & Francis |
Peer Reviewed | Peer Reviewed |
Volume | 93 |
Issue | 12 |
Pages | 3026-3049 |
DOI | https://doi.org/10.1080/00207179.2019.1575528 |
Keywords | Absolute stability, converging-input converging-state p roperty, integral projection models, incremental stability, infinite-dimensional disc rete-time systems, input-to-state stability, Lur’e systems, sampled-data systems |
Public URL | http://researchrepository.napier.ac.uk/Output/2677279 |
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Stability And Convergence Properties Of Forced Infinite-dimensional Discrete-time Lur'e Systems (accepted version)
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