摘要： 针对一类生产中存在严重非线性的复杂工业过程——pH中和过程,基于客观聚类思想,并结合Gustafson-Kessel聚类,提出一种新的T-S模糊建模方法。根据用户对建模性能的满意度要求,通过迭代模糊聚类,进行模型前提结构和参数的辨识。仿真结果表明,与传统的模糊聚类等方法相比,该方法不依赖于系统的先验知识和预先定义的模糊隶属度函数,具有较为精简的结构和更好的逼近性能,对数据中的噪声具有一定的鲁棒性。

关键词: 复杂工业过程, T-S模糊建模, 客观聚类, 模糊聚类, 满意聚类, pH中和过程

Abstract: For some manufacturing exists complex industrial processes with severe nonlinearity,named pH neutralization process,a new process T-S fuzzy modelling method via objective clustering idea,combined with Gustafson-Kessel(GK) clustering,is proposed.According to the satisfactory degree of modeling performance indexes,the premise structures and their parameters are identified through the iterated fuzzy clustering.Simulation results show that compared with the traditional fuzzy clustering,the proposed method does not rely on the prior-knowledge or defined fuzzy membership function,has a streamlined structure and better approximation performance,and is robust for the existing noise in data.

Key words: complex industrial process, T-S fuzzy modelling, objective clustering, fuzzy clustering, satisfactory clustering, pH neutralization process

中图分类号: 

• TP311