A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks


    Contributors:

    Publication date :

    1997-05-01


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English





    Direct Adaptive Control of Complex Dynamic Systems Using Neural Networks

    Liu, T. / Hu, D. / Lu, B. | British Library Online Contents | 1998


    Nonlinear Adaptive Control of Tiltrotor Aircraft Using Neural Networks

    Calise, Anthony J. / Chen, Robert T. N. / Rysdyk, Rolf | SAE Technical Papers | 1997


    Nonlinear adaptive control of tiltrotor aircraft using neural networks

    Rysdyk, Rolf / Calise, Anthony / Chen, Robert | AIAA | 1997


    Nonlinear Adaptive Control of Tiltrotor Aircraft Using Neural Networks

    Rysdyk, R. / Calise, A. J. / Chen, R. T. N. et al. | British Library Conference Proceedings | 1997