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Switched Two-Level and Robust Fuzzy Learning Control of an Overhead Crane

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  • Kao-Ting Hung
  • Zhi-Ren Tsai
  • Yau-Zen Chang

Abstract

Overhead cranes are typical dynamic systems which can be modeled as a combination of a nominal linear part and a highly nonlinear part. For such kind of systems, we propose a control scheme that deals with each part separately, yet ensures global Lyapunov stability. The former part is readily controllable by the PDC techniques, and the latter part is compensated by fuzzy mixture of affine constants, leaving the remaining unmodeled dynamics or modeling error under robust learning control using the Nelder-Mead simplex algorithm. Comparison with the adaptive fuzzy control method is given via simulation studies, and the validity of the proposed control scheme is demonstrated by experiments on a prototype crane system.

Suggested Citation

  • Kao-Ting Hung & Zhi-Ren Tsai & Yau-Zen Chang, 2013. "Switched Two-Level and Robust Fuzzy Learning Control of an Overhead Crane," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-12, April.
    • Handle: RePEc:hin:jnlmpe:712615
    DOI: 10.1155/2013/712615
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