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A T-S fuzzy iterative identification method via objective-satisfactory cluster analysis

机译:基于目标满意聚类分析的T-S模糊迭代识别方法

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A T-S fuzzy iterative identification method via Objective-Satisfactory Cluster Analysis is proposed in this paper. During the iteration, an Objective-Satisfactory Cluster Analysis algorithm, which combined the Enhanced Objective Cluster Analysis algorithm and the Gustafson-Kessel method is presented. Thus the accuracy and the robustness of the premise of T-S model are guaranteed. Then the consequent parameters are quickly estimated by the Stable Kalman Filter algorithm. The effectiveness of the presented method is proved by the pH-neutralization process.
机译:提出了一种基于目标满意聚类分析的T-S模糊迭代识别方法。在迭代过程中,提出了一种目标满意聚类分析算法,该算法结合了增强型目标聚类分析算法和Gustafson-Kessel方法。这样就保证了T-S模型前提的准确性和鲁棒性。然后,通过稳定卡尔曼滤波算法快速估计相应的参数。 pH中和过程证明了该方法的有效性。

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