基于改进最短邻聚类的最优模糊在线辨识

提出了一种改进的最短邻聚类算法。以输入输出空间为参考，依平均值法实时调整聚类中心，并结合能量函数判据，实现了模糊规则的增加，修改和删除，并保证模糊规则集的优良性。采用最优模糊辨识系统，作为离散时间非线性动态系统的自适应模糊控制器的基本组成单元，实现模型结构和参数的在线辨识及实时更新。仿真结果表明，基于该方法辨识的模糊系统结构简单，规则少，精度高，泛化性好。

Online optimal fuzzy identification using improved nearest-neighbor clustering method

To investigate online self-adaptive identification, a method based on improved nearest-neighborhood clustering with optimal fuzzy logic system was proposed. The advanced clustering way considered the input-output space, adjusted the centre point by calculating the means of the whole clustering space and judging the rule's deletion by potential function, and combined with optimal fuzzy logic system which proposed by WANG Li-xin. High identification speed and precision were achieved. The simulation result illustrates the effectiveness of the proposed method.