Prescribed-time non-overshooting tracking control for nonlinear systems via a time-scale transformation approach*
Mengnan Hao,
Ning Xu and
Ning Zhao
International Journal of Systems Science, 2026, vol. 57, issue 3, 804-815
Abstract:
This paper delves into addressing the issue of achieving non-overshooting tracking control within a prescribed time for a class of nonlinear systems. By employing a blow-up function and a time-scale transformation approach, the tracking error system is converted from the original time domain into a scaled system within the transformed time framework. Subsequently, a switching controller is then designed to ensure prescribed-time stability for the original tracking error system, which is achieved by applying a backstepping technique to analyze the global asymptotic stability of the scaled system. Additionally, conditions on the initial states of the tracking error system are provided to ensure the non-overshooting performance of nonlinear systems. Recommendations for selecting controller gains are also derived to guarantee non-overshooting prescribed-time stability under arbitrary initial conditions. Finally, the effectiveness of the proposed method is demonstrated through its application to a wheeled mobile robot system.
Date: 2026
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2025.2514587 (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:57:y:2026:i:3:p:804-815
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20
DOI: 10.1080/00207721.2025.2514587
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 ().