Finite-time adaptive fuzzy asymptotic tracking control for PMSMs with full-state constraints

Yang Yu, Lusong Ding and Wei Wang

International Journal of Systems Science, 2022, vol. 53, issue 5, 992-1003

Abstract: In this paper, a finite-time adaptive fuzzy control approach is developed for asymptotic tracking control of permanent magnet synchronous motors (PMSMs) with full-state constraints. Multiple nonlinear state-dependent functions are introduced in the control design, such that the rotor position, the rotor angular velocity and the currents of the d-q axis are confined to effective ranges. By combining backstepping control design with the finite-time control technique, a novel adaptive fuzzy tracking control is developed, which can accelerate the convergence speed and improve the robustness of the PMSM servo systems. Moreover, the asymptotic tracking control can be achieved with the aid of a scaling function. It is proven that all signals of the closed-loop system are uniformly ultimately bounded, and the position tracking error can converge to zero asymptotically in finite time. Finally, the simulation results are provided to verify the effectiveness of the proposed control approach, and some comparisons are given to show the rapid and accurate position tracking performance.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2021.1983065 (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:53:y:2022:i:5:p:992-1003

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

DOI: 10.1080/00207721.2021.1983065

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 ().