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.


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    Titel :

    Self-tuning Generalized Predictive Control applied to terrain following flight


    Beteiligte:
    Hess, R. A. (Autor:in) / Jung, Y. C. (Autor:in)

    Kongress:

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


    Erscheinungsdatum :

    1989-01-01


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch





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