In this paper, aerodynamic parameters have been estimated using neuro-fuzzy-based novel approach (ANFIS-Delta). ANFIS-Delta is an extension of a feed-forward neural network based Delta method. This method augments the philosophies of an adaptive neuro-fuzzy inference system (ANFIS) in the Delta method. The current work studies the comparison of ANFIS-Delta estimated results with the existing methods using the flight data gathered on the Hansa-3 research aircraft at IIT Kanpur and also, demonstrates the efficacy of the algorithm on DLR HFB-320 aircraft data. Further, the robustness of the ANFIS-Delta is examined using simulated data with known measurement noise of various strength and estimated parameters are compared with the wind tunnel extracted aerodynamic parameters.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    ANFIS-Delta method for aerodynamic parameter estimation using flight data


    Contributors:


    Publication date :

    2019-06-01


    Size :

    17 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






    Regularization regression methods for aerodynamic parameter estimation from flight data

    Kumar, Ajit / Ghosh, A.K. | Emerald Group Publishing | 2023


    Data-Driven Method based Aerodynamic Parameter Estimation from Flight Data (AIAA 2018-0768)

    Kumar, Ajit / Ghosh, Ajoy K. | British Library Conference Proceedings | 2018


    Aircraft Lateral Parameter Estimation from Flight Data with Unsteady Aerodynamic Modeling

    William R. Wells / Siva S. Banda / David L. Quam | AIAA | 1982