基于T-S模糊模型的辨识算法

提出一种新的基于T－S模糊模型的辨识算法。该算法可分为2步，第1步是比较粗糙的辨识，按子空间的线性程度来划分输入空间，规则前件参数由于空间的中心和大小决定，规则后件线性参数由最小二乘法确定2步是模的精细调整，利用梯度下降法调节隶属函数和规则后件的线性参数，仿真实验说明了该算法的有效性。

Identification Method Based on T-S Fuzzy Model

A new identification algorithm of Takagi Sugeno fuzzy model is proposed. The identification process consists of two steps. First, coarser identification is carried out. The input space is partitioned according to linear degree of the subspaces. The center and size of each subspace determine the parameters of the corresponding rule premise. The consequent parameters of every rule are identified by the least square method. Second, the initial model is fine tuned by the gradient descent algorithm. The objective function emphasizes accuracy of local model. A simulation example shows the effectiveness of the method.