Generalized Predictive Control (GPC) describes an algorithm for the control of dynamic systems in which a control input is generated which minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. Self-tuning GPC refers to an implementation of the GPC algorithm in which the parameters of the internal model(s) are estimated on-line and the predictive control law tuned to the parameters so identified. The self-tuning GPC algorithm is applied to a problem of rotorcraft longitudinal/vertical terrain-following flight. The ability of the algorithm to tune to the initial vehicle parameters and to successfully adapt to a stability augmentation failure is demonstrated. Flight path performance is compared to a conventional, classically designed flight path control system.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Self-tuning Generalized Predictive Control applied to terrain following flight


    Contributors:
    Hess, R. A. (author) / Jung, Y. C. (author)

    Conference:

    AIAA Guidance, Navigation and Control Conference ; 1989 ; Boston, MA, United States


    Publication date :

    1989-01-01


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English





    Nonlinear predictive control for terrain following

    Cui, H. / Geng, Y. / Yang, D. | British Library Online Contents | 1998


    Terrain-Following Guidance Based on Model Predictive Control

    Noh, Junyoung / Ahn, Hyungjoo / Lee, Jaeho et al. | Springer Verlag | 2022


    U-parameter design for terrain-following flight control

    WEI, YANG / SHEN, CHUN-LIN / DORATO,PETER | AIAA | 1993


    Automatic flight control system for automatic terrain-following

    KRACHMALNICK, F. / VETSCH, G. / WENDL, M. | AIAA | 1967