Backstepping is a powerful adaptive control method when applied to uncertain nonlinear systems. It provides an alternative to the traditional model‐reference adaptation system (MRAS) and self‐tuning regulation (STR) methods. The main advantage of the backstepping approach is the use of a recursive design procedure, which does not require that the parametric uncertainty should be matched by control inputs. The method is based on treating some state variables as virtual control Q, and designing intermediate control laws for them, which in turn are substituted to determine those state variables that are integrals of the first virtual set. In this way, adaptive control is carried out recursively by applying control to the parametric uncertainty appearing one integrator previously. Because of its departure from the certainty equivalence design, the back‐stepping integrator is said to cross the extended matching barrier that plagued the traditional Lyapunov‐based adaptive schemes.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Adaptive Backstepping Control


    Beteiligte:
    Tewari, Ashish (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    04.04.2016


    Format / Umfang :

    10 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Gaussian Process Adaptive Incremental Backstepping Flight Control

    Ignatyev, Dmitry / Shin, Hyo-Sang / Tsourdos, Antonios | TIBKAT | 2022


    Adaptive backstepping control for a convertible UAV

    Martinez, V. / Garcia, O. / Sanchez, A. et al. | IEEE | 2015


    A New Trend of Adaptive Control - Backstepping

    Miyasato, Y. | British Library Online Contents | 1994


    Model-Free Robust Backstepping Adaptive Cruise Control

    Yanan Zhang / Jiacheng Song | DOAJ | 2023

    Freier Zugriff

    Gaussian Process Adaptive Incremental Backstepping Flight Control

    Ignatyev, Dmitry / Shin, Hyo-Sang / Tsourdos, Antonios | AIAA | 2022