Modelling and neural adaptive vibration control for three-dimensional Timoshenko beam with output restrictions and external disturbances

Xueyan Xing and Jinkun Liu

International Journal of Systems Science, 2021, vol. 52, issue 9, 1850-1867

Abstract: In this paper, the dynamic modelling and adaptive boundary control of a three-dimensional Timoshenko beam are presented for vibration suppression. In order to ensure that no modal information is left out, partial differential equations (PDEs) are employed to describe the nonlinear dynamic characteristics of the system by applying the extended Hamilton’s principle. Based on the established model, barrier Lyapunov functions (BLFs) are utilised for dealing with system output restrictions. For practical consideration, parameter uncertainties and external disturbances are also taken into account. Under the proposed neural adaptive control scheme, undesirable elastic vibration of the three-dimensional Timoshenko beam is restricted and constrained within given bounds even subject to external perturbations, without needing to know any system parameters. The system stability is proved by the Lyapunov’s direct method. The control performance is verified via using numerical simulations.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2021.1871676 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:52:y:2021:i:9:p:1850-1867

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2021.1871676

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().