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Rule base identification toolbox for fuzzy controllers

机译:模糊控制器的规则库识别工具箱

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The performance of a fuzzy controller is determined in a great amount by the underlying rule base. In this paper, we present tuning methods implemented in our rule base identification and tuning toolbox. The toolbox is easy-to-use Matlab based software with graphical user interface. All the implemented tuning methods support the creation of low complexity and compact rule bases that contain only the most relevant rules. Besides, the clonal selection based method also can be applied in case of covering rule bases as well as for the tuning of input/output gains of fuzzy controllers.
机译:模糊控制器的性能在很大程度上取决于基础规则库。在本文中,我们介绍了在规则库标识和调整工具箱中实现的调整方法。该工具箱是基于Matlab的易于使用的软件,带有图形用户界面。所有已实现的调整方法都支持创建仅包含最相关规则的低复杂度和紧凑规则库。此外,基于克隆选择的方法还可以应用于覆盖规则库以及模糊控制器的输入/输出增益调整的情况。

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