Estimation-based iterative learning control (ILC) is applied to a parallel kinematic manipulator known as the Gantry-Tau parallel robot. The system represents a control problem where measurements of the controlled variables are not available. The main idea is to use estimates of the controlled variables in the ILC algorithm, and in the paper this approach is evaluated experimentally on the Gantry-Tau robot. The experimental results show that an ILC algorithm using estimates of the tool position gives a considerable improvement of the control performance. The tool position estimate is obtained by fusing measurements of the actuator angular positions with measurements of the tool path acceleration using a complementary filter. ; Funding Agencies|ELLIIT, Excellence Center at Linkoping - Lund in Information Technology; LCCC Linnaeus Center at Lund University; Vinnovas Industry Excellence Center LINK-SIC at Linkoping University


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    Title :

    Estimation-based ILC applied to a parallel kinematic robot



    Publication date :

    2014-01-01


    Remarks:

    ISI:000345728700001



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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