Resumen

GOMEZ PIZANO, DANIEL. COMPARISON OF FREQUENCY RESPONSE AND NEURAL NETWORK TECHNIQUES FOR SYSTEM IDENTIFICATION OF AN ACTIVELY CONTROLLED STRUCTURE. Dyna rev.fac.nac.minas [online]. 2011, vol.78, n.170, pp.79-89. ISSN 0012-7353.

System identification methodsare generally used to obtain the dynamic properties of structural systems. The dynamic properties are used for various purposes, such as model updating, structural health monitoring, and control synthesis. This paper presents the identification of an actively controlled structure with an active mass damper based on input-outputrelationships.The input signals include accelerations in the base of the structure and control force inputs while the output signals are the accelerations of the structure due to the inputs. In this paper, the system identification using frequency response functions iscompared with non-linear relationships obtained by using artificial neural networks (ANN) for bothasingle-input, single-output, and multiple-inputsingle-output (MISO) system. The results indicate that for the MISO structural system,the ANN technique providesa more accurate identification than identifications obtained with frequency responsemethods.

Palabras clave : Structural dynamics and control; system identification; frequency response; artificial neural networks; MISOsystem.

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