As a shuttle approaches the Space Station Freedom for a rendezvous, the shuttle's reaction control jet firings pose a risk of excessive plume impingement loads on Freedom solar arrays. The current solution to this problem, in which the arrays are locked in a feathered position prior to the approach, may be neither accurate nor robust, and is also expensive. An alternative solution is proposed here: the active control of Freedom's beta gimbals during the approach, positioning the arrays dynamically in such a way that they remain feathered relative to the shuttle jet most likely to cause an impingement load. An artificial neural network is proposed as a means of determining the gimbal angles that would drive plume angle of attack to zero. Such a network would be both accurate and robust, and could be less expensive to implement than the current solution. A network was trained via backpropagation, and results, which compare favorably to the current solution as well as to some other alternatives, are presented. Other training options are currently being evaluated.


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    Title :

    Neural Network for Positioning Space Station Solar Arrays


    Contributors:
    R. E. Graham (author) / P. P. Lin (author)

    Publication date :

    1994


    Size :

    8 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




    Neural Network for Positioning Space Station Solar Arrays

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