ANFIS-Delta method for aerodynamic parameter estimation using flight data. (June 2019)

• Record Type: Journal Article
• Authors: Kumar, Ajit; Ghosh, Ajoy Kanti
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 233:Number 8(2019)
• Page Start: 3016
• Page End: 3032
• Publication Date: 2019-06
• Subjects: ANFIS-Delta -- Delta method -- flight data -- fuzzy inference system -- parameter estimation; Aeronautics -- Periodicals; Astronautics -- Periodicals; Airplanes -- Design and construction -- Periodicals; Aerospace industries -- Periodicals; 629.1
• DOI: 10.1177/0954410018791621
• Languages: English
• ISSNs: 0954-4100

Abstract

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.