engleski

Neural Networks and Wavelets in Ships and Autopilots Identification

A referent model is used in autopilot design nowadays, where the parameters of the model are identified. Such model is not adjusted for a single particular ship. Introduction of self-learning neural networks enables individual approach to every ship and design of the best possible control for the particular ship. The basic mathematic and algorithms are discussed. Two types of neural networks are considered: feed-foreward networks (where neurons are organised in layers and typical application is in the non-linear static mapping) and recurrent network (where the output of neurons are fed back to the inputs of some neurons. These networks are used in non-linear dynamic systems). Wavelets' role in ships' identification is considered, as well as the wavelet networks' role, as the type of the neural networks. This article presents a general idea of wavelet and neural network application in ship's identification and modelling, as well as the possible usage of wavelets aboard ships.

wavelet; neural network; system identification; autopilot

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