Application of adaptive neuro fuzzy inference system (ANFIS) based genetic algorithm (GA) optimization to the problem of aerodynamic modeling and parameter estimation for aircraft is addressed. A neuro fuzzy based GA optimizer capable of predicting generalized force and moment coefficients employing measured motion and control variables only, without the requirement of conventional variables or their time derivatives, is proposed. Furthermore, it is shown that such a model can be used to extract equivalent stability and control derivatives of a rigid aircraft. Results are presented for aircraft to showcase the applicability of the proposed algorithm for both modeling and estimation of lateral parameters.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Lateral aircraft parameter estimation using neuro-fuzzy and genetic algorithm based method


    Contributors:


    Publication date :

    2017-03-01


    Size :

    2229093 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    LONGITUDINAL AIRCRAFT PARAMETER ESTIMATION USING NEURO-FUZZY AND GENETIC ALGORITHM BASED METHOD (AIAA 2017-3896)

    Roy, Abhishek Ghosh / Peyada, N. K. | British Library Conference Proceedings | 2017


    Aerodynamic parameter estimation using neuro-fuzzy model based method

    Kumar, Ajit / Saderla, Subrahmanyam / Ghosh, Ajoy Kanti | IEEE | 2017


    Aircraft Parameter Estimation Using Neural Network Based Algorithm

    Peyada, N. / Ghosh, A. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2009