Please use this identifier to cite or link to this item: https://doi.org/10.1049/iet-cta.2008.0138
Title: Feedforward control based on neural networks for disturbance rejection in hard disk drives
Authors: Ren, X.
Lai, C.Y.
Venkataramanan, V.
Lewis, F.L.
Ge, S.S. 
Liew, T.
Issue Date: 2009
Source: Ren, X., Lai, C.Y., Venkataramanan, V., Lewis, F.L., Ge, S.S., Liew, T. (2009). Feedforward control based on neural networks for disturbance rejection in hard disk drives. IET Control Theory and Applications 3 (4) : 411-418. ScholarBank@NUS Repository. https://doi.org/10.1049/iet-cta.2008.0138
Abstract: A feedforward control based on neural networks to attenuate the effect of external vibrations on the positioning accuracy of hard disk drives (HDDs) is presented. The adaptive neural network compensator utilises accelerometer signals to detect external vibrations. No information on the plant, sensor and disturbance dynamics is needed in the design of the adaptive neural network compensator. The stability of the proposed scheme is analysed by the Lyapunov criterion. Experimental results show that the tracking performance of HDDs can be improved significantly by using the feedforward controller when compared with the case without compensation. © The Institution of Engineering and Technology 2009.
Source Title: IET Control Theory and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/56039
ISSN: 17518644
DOI: 10.1049/iet-cta.2008.0138
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