This paper describes an approach for incorporating a neural network with real-time learning capability in a flight control architecture. The architecture is also applicable, in general, for the control of processes described by nonlinear differential equations of motion in which there exists a control for each degree of freedom. The main features are that the defining equations of motion for the process to be controlled are poorly known with respect to their functional forms, and that the functional forms, themselves, may undergo sudden and unexpected variation. It is well known that such systems are difficult to control, particularly when the effect of the control action enters nonlinearly. Numerical results based on 6DOF simulations of a high performance aircraft are presented to illustrate the potential benefits of incorporating neural networks as a part of a flight control system architecture.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Neural networks in nonlinear aircraft flight control


    Contributors:


    Publication date :

    1996-07-01


    Size :

    639500 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Nonlinear flight control using neural networks

    Kim, Byoung / Calise, Anthony | AIAA | 1994



    Nonlinear Flight Control Using Neural Networks

    Byoung S. Kim / Anthony J. Calise | AIAA | 1997


    Nonlinear Flight Control Using Neural Networks

    Kim, B. / Calise, A. / AIAA | British Library Conference Proceedings | 1994


    Nonlinear Flight Control Using Neural Networks

    Kim, B.S. | Online Contents | 1997