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.
|Number of pages||8|
|Publication status||Published - 18 Nov 2009|
|Event||Proceedings of the International Joint Conference on Neural Networks - |
Duration: 18 Nov 2009 → …
|Conference||Proceedings of the International Joint Conference on Neural Networks|
|Period||18/11/09 → …|