[1]王庆超,张健中.基于Hammerstein模型的连续搅拌反应釜非线性预测控制[J].南京理工大学学报(自然科学版),2010,(05):618-623.
 WANG Qing-chao,ZHANG Jian-zhong.Nonlinear Predictive Control for Continuous Stirred-tank Reactor Using Hammerstein Model[J].Journal of Nanjing University of Science and Technology,2010,(05):618-623.
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基于Hammerstein模型的连续搅拌反应釜非线性预测控制
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2010年05期
页码:
618-623
栏目:
出版日期:
2010-10-31

文章信息/Info

Title:
Nonlinear Predictive Control for Continuous Stirred-tank Reactor Using Hammerstein Model
作者:
王庆超;张健中;
哈尔滨工业大学能源科学与工程学院
Author(s):
WANG Qing-chaoZHANG Jian-zhong
School of Energy Science and Engineering,Harbin Institute of Technology,Harbin 150001,China
关键词:
非线性预测控制 Hammerstein模型 最小二乘支持向量机 连续搅拌反应釜
Keywords:
nonlinear predictive control Hammerstein model least square support vector machine continuous stirred-tank reactors
分类号:
TP273
摘要:
该文针对化工过程中广泛使用的连续搅拌反应釜(CSTR),提出一种基于最小二乘支持向量机Hammerstein模型的非线性预测控制方法。Hammerstein模型的非线性环节采用最小二乘支持向量机逼近,线性环节则采用外因输入自回归模式(ARX)结构。基于此模型结构设计非线性模型预测控制器,将非线性预测控制问题转化为线性模型的预测控制和非线性模型的求逆问题,进而给出了预测控制律以及非线性环节逆模型的构造方法。对CSTR的仿真结果表明:与传统的非线性模型预测控制以及PI控制器相比,该文方法精度更高,能够有效跟踪控制反应物浓度。
Abstract:
A nonlinear predictive control method based on a least square support vector machine Hammerstein model is proposed for a continuous stirred-tank reactor(CSTR).A least square support vector machine(LSSVM) is used to approximate the static nonlinearity of the Hammerstein model,and a linear autoregressive model with exogenous input(ARX) is used to represent the linear block.A nonlinear predictive controller is designed based on the Hammerstein model of CSTR.The nonlinear predictive control is converted into a linear predictive control model and a nonlinear inverse model.A predictive control law is deduced,and the inverse model of the nonlinear part is constructed consequently.The proposed control scheme is compared with the traditional nonlinear predictive control and PI controller.Simulation results of CSTR indicate that the proposed nonlinear predictive controller has the highest accuracy in set point tracking of product concentration in comparison with the other two controllers.

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金( 60574022)
作者简介: 王庆超( 1950- ) , 男, 教授, 博士生导师, 主要研究方向: 复杂大系统控制、智能控制等, Email:wangqingchao@hit.edu.cn。
更新日期/Last Update: 2012-11-02