Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.


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    Titel :

    An Adaptive Critic Approach to Reference Model Adaptation


    Beteiligte:
    Krishnakumar, K. (Autor:in) / Limes, G. (Autor:in) / Gundy-Burlet, K. (Autor:in) / Bryant, D. (Autor:in)

    Kongress:

    AIAA GNC Conference ; 2003 ; Austin, TX, United States


    Erscheinungsdatum :

    2003-05-29


    Medientyp :

    Preprint


    Format :

    Keine Angabe


    Sprache :

    Englisch




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