Disturbance and friction compensations in hard disk drives using neural networks / Lai, Chow Yin in IEEE transactions on industrial electronics, Vol. 57 N° 2 (Fevrier 2010)  

Public ISBD [article]  inIEEE transactions on industrial electronics > Vol. 57 N° 2 (Fevrier 2010) . - pp. 784 - 792 Titre : Disturbance and friction compensations in hard disk drives using neural networks Type de document : texte imprimé Auteurs : Lai, Chow Yin, Auteur ; Lewis, Frank L., Auteur ; Venkataramanan, Venkatakrishnan, Auteur Article en page(s) : pp. 784 - 792 Note générale : Génie électrique Langues : Anglais (eng) Mots-clés : Disturbance feedforward Friction compensation Hard disk drives (HDDs) Neural networks (NNs) Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : In this paper, we show that by using two adaptive neural networks (NNs), each of which is tailored for a specific task, the tracking performance of the hard-disk-drive (HDD) actuator can be significantly improved. The first NN utilizes accelerometer signal to detect external vibrations and compensates for its effect on HDD position via feedforward action. The second NN is designed to compensate for pivot friction. The appealing advantage of the NN compensators is that the design does not involve any information on the plant, sensor, disturbance dynamics, and friction model. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Experimental results show that the tracking performance of the HDDs can be improved significantly with the use of the NN compensators as compared to the case without compensation. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5173528 [article] Disturbance and friction compensations in hard disk drives using neural networks [texte imprimé] / Lai, Chow Yin, Auteur ; Lewis, Frank L., Auteur ; Venkataramanan, Venkatakrishnan, Auteur . - pp. 784 - 792. Génie électrique Langues : Anglais (eng) in IEEE transactions on industrial electronics > Vol. 57 N° 2 (Fevrier 2010) . - pp. 784 - 792 Mots-clés : Disturbance feedforward Friction compensation Hard disk drives (HDDs) Neural networks (NNs) Index. décimale : 621.38 Dispositifs électroniques. Tubes à électrons. Photocellules. Accélérateurs de particules. Tubes à rayons X Résumé : In this paper, we show that by using two adaptive neural networks (NNs), each of which is tailored for a specific task, the tracking performance of the hard-disk-drive (HDD) actuator can be significantly improved. The first NN utilizes accelerometer signal to detect external vibrations and compensates for its effect on HDD position via feedforward action. The second NN is designed to compensate for pivot friction. The appealing advantage of the NN compensators is that the design does not involve any information on the plant, sensor, disturbance dynamics, and friction model. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Experimental results show that the tracking performance of the HDDs can be improved significantly with the use of the NN compensators as compared to the case without compensation. DEWEY : 621.38 ISSN : 0278-0046 En ligne : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5173528

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