Design of experiments for MR damper modelling

Authors:
Jorge Lozoya-Santos;Ruben Morales-Menendez;Ricardo Ramirez-Mendoza
Affiliations:
Tecnológico de Monterrey;Tecnológico de Monterrey;CIDyT, Tecnológico de Monterrey
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

Citing 3
Cited 0

System identification

System identification
Modelling of a magneto-rheological damper by evolving radial basis function networks

Engineering Applications of Artificial Intelligence
Identification of semi-physical and black-box non-linear models: the case of MR-dampers for vehicles control

Automatica (Journal of IFAC)

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Abstract

An approach to find out the training inputs for identification of a Magneto-Rheological (MR) damper is proposed. Reduction of overuse of the damper, number of experiments and configurations of training inputs are main features of this approach. Experimental validation with a commercial MR damper was carried out.Main results show inputs configuration with modulated frequency at fixed amplitude displacement, and random amplitude step with fixed period generate key information. A feed-forward neural network was selected as model emulator. Modelling results showed an error-to-signal ratio lower than milli-thousands.