Satellite Attitude Acquisition Using a Neural Network Controller
نویسندگان
چکیده
Neural networks are non-linear functional approximators, and natural candidates to be used in nonlinear systems control. Satellite nominal attitude control dynamics is an example of non-linear system where conventional control has been applied sucessfully since the early space age. However, conventional control like the PD (proportional and derivative of the error) can only guarantee robustness to work in a small region around the reference or nominal attitude. This certaninly is not the case of an attitude acquisition, where large maneuvers are commanded autonomously in order to point the satellite close to a nominal attitude. Searching for a solution that overcomes this limitation, in this work it is investigated the possibility of performing satellite attitude acquisition control by means of an artificial neural net. It is employed the feedback error learning method in order to train the network with the inverse dynamics. A simulated example of an attitude acquisition of a satellite with deploying solar arrays is presented.
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