基于模糊神经网络分类器的精馏塔温度控制器设计  

Design of distillation column temperature controller based on fuzzy neural network classifier

作　　者：谷玉凯[1] 杨滁光[2] 王华强[1] 王健波[1] 

机构地区：[1]合肥工业大学电气与自动化工程学院,安徽合肥230009 [2]安徽安利合成革股份有限公司,安徽合肥231202

出　　处：《合肥工业大学学报（自然科学版）》2012年第1期41-44,137,共5页Journal of Hefei University of Technology：Natural Science

基　　金：国家自然科学基金资助项目(60974022);合肥工业大学产学研校企合作资助项目(10-469)

摘　　要：文章对精馏塔温度控制中所遇到的参数耦合严重、非线性高、数学模型难以建立的问题,提出了一个基于模糊神经网络分类器的控制方案,以精馏塔温度、流量、液位作为输入,导热油阀门开度作为输出,通过对人工操作的自适应学习和模糊化处理,实现对精馏塔温度的智能控制。实验结果表明,该方案能够模仿人工操作,智能学习的精度很高。In view of the problems in the temperature control of distillation column such as serious parameters coupling,high nonlinearity and difficulty in building mathematical model,a novel control scheme based on fuzzy neural network classifier is proposed in this paper.Taking the temperature,flow and liquid level as input and the valve opening as output,the intelligent control of distillation column temperature is achieved through manually operated self-adaptive learning and fuzzification processing.Experimental results show that this scheme can imitate the manual operation,and the intelligent learning is in high precision.

关 键 词：精馏塔 温度控制 模糊神经网络分类器 自适应学习 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]