首页 | 本学科首页   官方微博 | 高级检索  
     

基于支持向量机和粒子群算法的软测量建模
引用本文:刘瑞兰,牟盛静,苏宏业,褚健.基于支持向量机和粒子群算法的软测量建模[J].控制理论与应用,2006,23(6):895-899.
作者姓名:刘瑞兰  牟盛静  苏宏业  褚健
作者单位:1. 南京邮电大学,自动化学院,江苏,南京,210003
2. 新加坡高性能计算研究所,新加坡,117528
3. 浙江大学,先进控制研究所,工业控制技术国家重点实验室,浙江,杭州,310027
基金项目:国家863计划资助项目(2001AA413020),国家杰出青年科学基金(60025308).
摘    要:针对PX氧化过程中的4-CBA浓度的估计问题,提出了基于支持向量机和粒子群算法来估计机理模型参数的方法.用支持向量机回归来提取特征样本,这些少量的特征样本估计机理模型参数可以减少计算时间,同时避免了人工随机试凑法选择训练样本的盲目性.采用粒子群算法来估计非线性机理模型的参数,可以避免传统方法对初始点和样本的依赖.工业实例表明,本文提出的方法是有效的.

关 键 词:支持向量机  特征样本  粒子群优化算法  PTA氧化过程  软测量
文章编号:1000-8152(2006)06-0895-05
收稿时间:2005-04-19
修稿时间:2005-04-192005-12-12

Modeling soft sensor based on support vector machine and particle swarm optimization algorithms
LIU Rui-lan,MU Sheng-jing,SU Hong-ye,CHU Jian.Modeling soft sensor based on support vector machine and particle swarm optimization algorithms[J].Control Theory & Applications,2006,23(6):895-899.
Authors:LIU Rui-lan  MU Sheng-jing  SU Hong-ye  CHU Jian
Affiliation:College of Automation, Nanjing University of Post &Telecommunication, Nanjing Jiangsu 210003, China; Institute of High Performance Computing, 117528, Singapore; National Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University, Hangzhou Zhejiang 310027, China
Abstract:The estimation of 4-CBA (carboxybenzaldchydc) concentration in industrial PTA (purified terephthalic acid) oxidation process is of fundamental importance in process monitoring,advanced control and optimization.The support vector machine (SVM) and particle swarm optimization (PSO) algorithms are used to estimate the parameters of the first principle model.The training set for estimating the parameters is the feature subset selected by SVM regression algorithm, which overcomes the drawback of the trail-and-error method.Parameter estimation method based on the PSO algorithm is also used to avoid dependence on initial parameters and training samples.By use of real industrial data,the simulation results show that the presented method is effective for modeling the soft sensor of 4-CBA concentration in industrial PTA oxidation process.
Keywords:support vector machine  feature subset  particle swarm optimization algorithm  PTA(purified terephthalic acid)oxidation process  soft sensor
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《控制理论与应用》浏览原始摘要信息
点击此处可从《控制理论与应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号