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The effectiveness of a controller architecture, which combines adaptive feedforward neural networks with feedback linearization, has been demonstrated on a variety of flight vehicles. The boundedness of tracking error and control signals is guaranteed. The architecture can accommodate both linear-in-the-parameters networks, as well as single-hidden-layer perceptron neural networks. Both theoretical and experimental research is planned to expand and improve the applicability of the approach, and to demonstrate practical utility in the areas of cost reduction and improved flight safety.
Calise et al. (Tue,) studied this question.