Real-time Learning of Aircraft Parameters Using Recursive Least-squares to Train Rbf Networks

Abstract

We describe a real-time algorithm for learning aircraft parameters to be used by an adaptive controller. Learning consists of training a collection of radial basis function neural networks to approximate the incoming data stream in the least-squares sense. Only the heights of the basis functions are trained; heuristics are used to find their centers and… (More)

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