Improvement of Control Performance for Low-Dimensional Number of Fuzzy Labelings Applying Simplified Inference Method

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  • 簡略化推論法を適用した低次元分割におけるファジィ制御性能の改善
  • カンリャクカ スイロンホウ オ テキヨウシタ テイジゲン ブンカツ ニ オケル

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Abstract

One of the important concept in fuzzy control is fuzzy inference, and the “simplified inference method” which is aimed at increasing the speed of the fuzzy inference has recently been used to realize a high-speed fuzzy controller. In designing a fuzzy controller, a high dimension such as 7×7 or 5×5 partitions is frequently used for the number of fuzzy labelings. However, as the number of fuzzy labelings increases, the number of control parameters increases rapidly and tuning of the fuzzy controller becomes difficult. Therefore, a fuzzy controller is required to be partitioned into a low-dimensional number of fuzzy labelings such as 3×3 partitions.<br>With this in mind, first, a method of improving the control performance for a low-dimensional number of fuzzy labelings using the “simplified inference method” which enables high-speed inference is proposed in this paper. Next, the effectiveness of this improvement method is investigated based on the results of several simulations where a first-order lag system with dead time, which is a representative model for plant characteristics, is used as the controlled system.

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