引用本文:[点击复制]
[点击复制]
【打印本页】 【在线阅读全文】【下载PDF全文】 查看/发表评论下载PDF阅读器关闭

←前一篇|后一篇→

过刊浏览    高级检索

本文已被:浏览 2921次   下载 179 本文二维码信息
码上扫一扫!
基于机理模型的精馏塔组分非线性预测控制算法
朱燎原,张小艳,赵均,徐祖华
0
(浙江大学控制科学与工程学院, 工业控制国家重点实验室, 杭州 310027)
摘要:
当精馏塔存在如进料流量、进料成分扰动,或是负荷发生大范围扰动变化时,常规控制器难以保持控制品质。本文提出了一种基于机理模型的精馏塔组分非线性预测控制方法;针对精馏塔组分不能在线测量的问题设计了扩展卡尔曼滤波器,使用可测的状态温度估计组分,并结合慢频的分析化验值对组分进行联合校正。仿真结果表明了该算法的有效性,在系统存在失配或进料扰动的情况下,可以取得良好的控制效果。
关键词:  精馏塔  非线性预测控制  扩展卡尔曼滤波
DOI:10.14135/j.cnki.1006-3080.2017.03.018
投稿时间:2016-10-31
基金项目:国家自然科学基金(61273145,61273146)
Nonlinear Predictive Control Algorithm for Distillation Column Component Based on Mechanism Model
ZHU Liao-yuan,ZHANG Xiao-yan,Zhao Jun,XU Zu-hua
(National Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China)
Abstract:
When there exist disturbances,e.g.,the fractionator feed and components or large load,it is difficult for conventional controller to exhibit better performance.This paper presents a nonlinear predictive control algorithm for distillation component via mechanism model.Aiming at the problem that components cannot be online measured,the extended Kalman filter and accessible temperature are utilized to estimate components,which is further updated by combining with laboratory analysis of the low frequency value.The simulation results show that the proposed algorithm can attain better control performance for model mismatch or feed disturbances.
Key words:  distillation  nonlinear model predictive control  extended Kalman filter

用微信扫一扫

用微信扫一扫