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Balancing control energy and tracking error for fuzzy rule emulated adaptive controller

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Abstract

In this article, an adaptive controller, which can minimize both tracking error and control energy, is introduced by fuzzy rule emulated network (FREN) for a class of non-affine discrete time systems. The controlled plant can be assumed as fully unknown system dynamic. Only the estimated boundary of pseudo partial derivative (PPD) is required for an on-line learning phase. The update law is derived to guarantee the convergence of tuned parameters. Lyapunov techniques are utilized to demonstrate the performance of a closed-loop system regarding the integration of the infinite cost function. The computer simulation and electronic circuit system validate the effectiveness of the proposed control scheme.

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Authors and Affiliations

  1. Department of Robotic and Advanced Manufactory, CINVESTAV-Saltillo, Ramos Arizpe, 25900, Mexico

    Chidentree Treesatayapun

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  1. Chidentree Treesatayapun
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Correspondence to Chidentree Treesatayapun.

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Treesatayapun, C. Balancing control energy and tracking error for fuzzy rule emulated adaptive controller. Appl Intell 40, 639–648 (2014). https://doi.org/10.1007/s10489-013-0493-x

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  • DOI: https://doi.org/10.1007/s10489-013-0493-x

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