The invention discloses a flying wing unmanned aerial vehicle control surface fault diagnosis method based on a neural network adaptive observer, and belongs to the technical field of calculation, reckoning or counting. Aiming at the comprehensive characteristics of strong coupling, strong nonlinearity and the like of an advanced layout flying-wing unmanned aerial vehicle, decoupling processing and linear analysis are difficult to carry out by adopting a conventional method after an actuator fault occurs, the invention provides a fault diagnosis method based on a neural network adaptive observer, so that the control surface characteristics of the flying-wing unmanned aerial vehicle are effectively processed; and the real-time performance and the fault estimation precision of the fault diagnosis system are ensured.

    本发明公开了一种基于神经网络自适应观测器的飞翼无人机操纵面故障诊断方法,属于计算、推算或计数的技术领域。本发明针对先进布局飞翼无人机的强耦合及强非线性等综合特性,出现执行器故障后难以采用常规方法进行解耦处理和线性化分析,提出基于神经网络自适应观测器的故障诊断方法,有效处理飞翼无人机的舵面特性,保证故障诊断系统的实时性和故障估计精度。


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    Title :

    Flying wing unmanned aerial vehicle control surface fault diagnosis method based on neural network adaptive observer


    Additional title:

    一种基于神经网络自适应观测器的飞翼无人机操纵面故障诊断方法


    Contributors:
    ZHENG FENGYING (author) / XU MENGYUAN (author) / XU KAIZHAO (author)

    Publication date :

    2023-01-31


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B64C AEROPLANES , Flugzeuge / B64D Ausrüstung für Flugzeuge , EQUIPMENT FOR FITTING IN OR TO AIRCRAFT / B64U / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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