Neural network based learning control of PUMA 560 manipulator

E. S. C. Tzimopoulos, V. M. Becerra

    Research output: Contribution to conferencePaperpeer-review

    Abstract

    This paper investigates the practical application of neural networks with online learning for robot manipulator control. Experiments have been performed with a PUMA Unimate 560 industrial manipulator with reference signals of increasing complexity. The results presented demonstrate features of the proposed framework such as accurate trajectory tracking, online learning, and bounded weights, which guarantee closed loop stability.
    Original languageEnglish
    Publication statusPublished - 2006
    EventInternational Control Conference (ICC2006) - Glasgow, United Kingdom
    Duration: 30 Aug 20061 Sep 2006

    Conference

    ConferenceInternational Control Conference (ICC2006)
    CountryUnited Kingdom
    CityGlasgow
    Period30/08/061/09/06

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