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.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    An Adaptive Critic Approach to Reference Model Adaptation


    Contributors:

    Conference:

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


    Publication date :

    2003-05-29


    Type of media :

    Preprint


    Type of material :

    No indication


    Language :

    English




    An Adaptive Critic Approach to Reference Model Adaptation

    Krishnakumar, Kalmanje / Limes, Greg / Gundy-Burlet, Karen et al. | AIAA | 2003


    Online Adaptive Critic Flight Control

    Ferrari, S. | Online Contents | 2004


    Online Adaptive Critic Flight Control

    Silvia Ferrari / Robert Stengel | AIAA | 2004