Abstract

SANCHEZ FERNANDEZ, Luis Pastor. Patterns of First and Second Order Systems in Virtual Instrumentation Environment. Comp. y Sist. [online]. 2003, vol.7, n.2, pp.92-101. ISSN 2007-9737.

This paper presents the analysis of patterns which allow to recognize dynamic models of first and second order systems by means of a backpropagation neuronal network. The neuronal network is of three layers. The input layer has 30 neurons, the hidden layer has 11 neurons and the exit layer has 4 neurons. A circular buffer is used to store the n last acquired values from each variable. The stored data are filtered digitally before executing the neuronal network. The conversion of the sampling frequency does possible to obtain 30 points. The exit of the neuronal network will indicate the most appropriate model. Software is developed using Lab VIEW and DLL written in DELPHI and C.

Keywords : virtual; neuronal network; patterns; prediction; supervision.

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