Motion control using support vector machine-based learning feed-forward

Bas de Kruif, Theo J.A. de Vries

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    The tracking performance of a motion system increases drastically, if in addition to a feedback compensator, a feed-forward controller is applied. This feed-forward controller should be equal to the (stable part of the) inverse of the plant. However an accurate inverse is generally difficult to obtain, e.g. due to plant non-linearities. Learning Feed-Forward Control can help to overcome this difficulty. For the learning a function approximator is required. Support Vector Machines can be used as a function approximator in the LFFC setting. When using a SVM, a non-linear function is approximated by a linear approximation in the feature space, which is a (non-linear) mapping of the input-space. The mapping from input space to feature space determines the set of functions from which the function approximator can choose. The perfor- mance of LFFC is influenced by this set of functions. Mappings that give rise to a set of function that have a support on the complete input-space are preferred over mappings that have a local support.
    Original languageEnglish
    Title of host publicationWESIC 2001
    Subtitle of host publicationWorkshop on European Scientific and Industrial Collaboration
    EditorsJ. van Amerongen, J.B. Jonker, P.P.L. Regtien
    Place of PublicationEnschede
    PublisherDrebbel Institute for Mechatronics
    Number of pages10
    ISBN (Print)90-365-16102
    Publication statusPublished - 27 Jun 2001
    Event3rd Workshop on European Scientific and Industrial Collaboration, WESIC 2001 - University of Twente, Enschede, Netherlands
    Duration: 27 Jun 200129 Jun 2001
    Conference number: 3


    Workshop3rd Workshop on European Scientific and Industrial Collaboration, WESIC 2001
    Abbreviated titleWESIC

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