UAVs are quad-copter unmanned helicopters, They been the subject of growing importance and are widely used in several fields; for this reason and to improve their performance, in this article we have proposed an algorithm based on the ANFIS. The genetic algorithms is used in order to optimize the ANFIS parameters and thereby ensure its learning, which maintains the ability for self-organization and self-learning. The proposed control scheme aims to implement good capabilities such as the description of qualitative knowledge, a learning mechanism and direct processing of quadcopter helicopter quantitative data. This control is adopted the precision and time of adjustment. On the other hand, If the position and attitude deviation becomes relatively smaller, The PID command will be used to limit this error. Experimental results indicate that the proposed ANFIS control algorithm has good performance in the flight process.


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    Titel :

    Improvement of the Stability Performance of a Quad-Copter Helicopter by a Neuro-Fuzzy Controller


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Bououden, Sofiane (Herausgeber:in) / Chadli, Mohammed (Herausgeber:in) / Ziani, Salim (Herausgeber:in) / Zelinka, Ivan (Herausgeber:in) / Baladji, Djalal (Autor:in) / Lamamra, Kheireddine (Autor:in) / Batat, Farida (Autor:in)

    Kongress:

    International Conference on Electrical Engineering and Control Applications ; 2019 ; Constantine, Algeria November 19, 2019 - November 21, 2019



    Erscheinungsdatum :

    30.09.2020


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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