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. © 2009 IEEE.
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CITATION STYLE
Lozoya-Santos, J., Morales-Menendez, R., & Ramirez-Mendoza, R. (2009). Design of experiments for MR damper modelling. In Proceedings of the International Joint Conference on Neural Networks (pp. 1915–1922). https://doi.org/10.1109/IJCNN.2009.5179003
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