Abstract
A new hybrid fuzzy logic and neural network control architecture is proposed and its application to attitude control of a spacecraft docking system is described. The controller uses fuzzy logic control to construct a knowledge base of control rules and learns by updating its prediction of the physical systems behavior and fine tuning a control knowledge base. It is applicable to control problems for which the analytical models of the process are unknown. >
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