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In this paper, a neural-approximation-based robust adaptive control methodology is proposed for a constrained flexible air-breathing hypersonic vehicle (FAHV) subject to parametric uncertainties. To reduce the computational costs, only two radial basis function neural networks (RBFNNs) are applied to approximate the lumped unknown nonlinearities of the velocity subsystem and the altitude subsystem,...
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