Abstract
A method for using artificial neural networks for the direct adaptive control of large space structures (LSS) with partially unknown dynamics is investigated. A neuromorphic controller is developed, and the authors demonstrate how it is applied to the vibration suppression problem for LSS. A key result is that measurements of all of the system states are not required, but rather only the output measurements and their delayed values. The neuromorphic controller (NMC) is represented by a fixed topology feedforward neural network whose weights are adjusted in real-time by a nonlinear recursive least square algorithm. Several simulation examples are given for the problem of vibration suppression for a subsystem model of the Jet Propulsion Laboratory/AFAL flexible spacecraft simulator. >
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