一种区间二型T-S模糊模型辨识算法  

An Interval Type-2 T-S Fuzzy Model Identification Algorithm

作　　者：尹健 Yin Jian(Huaneng Power International,INC.Jiangsu Nantong Power Plant,Jiangsu,Nantong,226001,China)

机构地区：[1]华能国际电力江苏能源开发有限公司南通电厂,江苏南通226001

出　　处：《仪器仪表用户》2022年第10期100-103,共4页Instrumentation

摘　　要：针对基于传统一型T-S模糊模型的系统辨识方法在处理系统不确定性方面的缺陷,提出了一种区间二型T-S模糊模型辨识算法。该算法首先利用区间二型模糊C均值聚类进行前件参数的辨识,在区间二型模糊集合的降阶部分,采用一种直接降阶算法,避免了传统KM降阶算法的迭代过程。其次,利用最小二乘算法进行T-S模糊模型的后件参数辨识。通过两个典型的非线性系统的仿真实例表明,本文的辨识算法具有较高的辨识精度。In according with the shortcomings of system identification based on the traditional type-1 T-S fuzzy model in dealing with system uncertainties,an interval type-2 T-S fuzzy model identification algorithm is proposed.Firstly,interval type-2 fuzzy c-means clustering is applied in antecedent parameters identification,and a direct type reduction algorithm is adopted to avoid the iterative process of the traditional KM type reduction algorithm.Then,the least square algorithm is applied in identification of consequent parameters of T-S fuzzy model.The simulation results of two typical nonlinear systems show that the proposed identification algorithm has higher identification accuracy.

关 键 词：区间二型模糊集合 区间二型模糊C-均值 模糊系统辨识 T-S模糊模型 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]