A novel use of state estimation methods as initial input for a landing response analysis is proposed in this work. Six degrees of freedom (DOF) non-linear landing response model is conceived by considering longitudinal dynamics of aircraft as a rigid body with heave-and-pitch motions coupled onto a bicycle landing gear† arrangement. The DOF for each landing gear consist of vertical and longitudinal motions of un-sprung mass, considering strut bending flexibility. The measurement data for state estimation is obtained for three landing cases using non-linear flight mechanics model interfaced with pilot-in-loop simulation. State estimation methods such as Upper Diagonal Adaptive Extended Kalman Filter (UD-AEKF) with fuzzy-based adaptive tuning and Un-scented Kalman Filter (UKF) were adapted for landing maneuver problem. On the basis of estimation error metrics, aircraft state from UKF is considered during onset of touchdown. These estimated states are used as an initial condition for the six DOF non-linear landing response model, numerically solved in Matlab environment. The dynamic responses such as displacement, velocity, and acceleration for the aircraft and the loads on landing gears such as vertical and drag (spin-up and spring-back) forces were presented. The uncertainty in noisy measurement data being over or under quantified and the sensitivity of landing loads toward variation in key aircraft state, such as vertical descent rate, are cohesively brought out. The significance of the methodology evolved in this work is highlighted in the context of critical event such as “hard landing” that demands accurate landing loads estimation for structural integrity assessment.


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    Title :

    Landing Response Analysis on High-Performance Aircraft* Using Estimated Touchdown States


    Additional title:

    Sae Int. J. Aerosp


    Contributors:

    Published in:

    Publication date :

    2019-04-08


    Size :

    17 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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