Fuzzy logic deals with the imprecision of natural world data which can not be described by precise equations and traditional logic. It is constructed around the idea of a set in which the membership is a matter of degree rather than yes or no. Though known for more than 30 years, the value of fuzzy logic has been appreciate only recently through applications mainly in consumer appliances in Japan. Fuzzy logic principles have been investigated at Johnson Space Center for several space applications such as translational and rotational control of spacecraft, camera tracking system, auto focusing of microscope, temperatur control in a payload module, tether length control and robotics manipulator control. Neural networks known for almost, a half-century deal with the complexities of the natural world data by generalizing from prototypes or samples in much the same as humans extrapolate from one experience to similar situations. Neural networks have been studied for fault diagnosis and health monitoring of space operations and have been exetndedto icludetime corelateddata adcreate theSpace-Time Neural Nework. Neural netwoks have been combined wih fuzzy logic investigate the daptive decision making system for translational and rotational control. This paper describes some of the space applications of fuzzy logic and neural networks including tether skip-rope identification using Space-Time-Neural Network. It also describes the tools developed at Johnson Space Center to support such investigations.


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    Title :

    Fuzzy logic and neural networks in space applications


    Additional title:

    Fuzzy-Logik und neuronale Netze in Raumfahrtanwendungen


    Contributors:
    Jani, Y. (author) / Aldridge, J. (author)


    Publication date :

    1993


    Size :

    37 Seiten, 21 Bilder, 4 Tabellen, 39 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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