This paper studies the Lyapunov-based adaptive neural network optimized tracking control problem for a class of unmanned fire fighting robots. Firstly, by reasonably simplifying the unmanned fire fighting robot (UFFR) and combining it with its actual working scene, a novel system model is created that takes into consideration both system uncertainties and external disturbances, including unknown friction factors and drag force. Then, the optimized tracking control scheme for the UFFR is devised by integrating both adaptive neural networks and the backstepping technique. The objective of introducing adaptive neural network technique is to overcome the challenge posed by solving the Hamilton-Jacobi-Bellman (HJB) equation. Based on Lyapunov stability theory, it is demonstrated that all signals in the closed-loop system are semi-globally ultimately bounded and the output variables follow the reference signals to the desired accuracy. In the end, to validate the effectiveness of our designed control scheme, numerical simulations and practical platform experiments have been conducted. To ensure repeatability, our codes are open sourced on Github: https://github.com/JiannanChen/RL-based-OBC-of-UFFR.git


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Lyapunov-Based Adaptive Neural Network Optimized Backstepping Control of Uncertain Unmanned Fire Fighting Robot


    Beteiligte:
    Chen, Jiannan (Autor:in) / Hua, Changchun (Autor:in) / Mu, Dianrui (Autor:in) / Sun, Fuchun (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.08.2025


    Format / Umfang :

    1240786 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Fire-fighting and fire-extinguishing robot and unmanned aerial vehicle combined fire fighting system

    WANG LEI / ZHANG XINGQI / FU GUOXIN et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Unmanned fire fighting device based on 5G network

    LI QINGLEI | Europäisches Patentamt | 2021

    Freier Zugriff

    Fire-fighting unmanned ship

    GU YIN / ZHAO KE / LIU YUAN et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Fire-fighting unmanned aerial vehicle for fire-fighting fixation

    GENG JIAN | Europäisches Patentamt | 2020

    Freier Zugriff