重庆大学学报2017，Vol.40Issue(9)：76-82,7.DOI:10.11835/j.issn.1000-582X.2017.09.009
基于SVR的焦炉冷鼓系统预测控制
Predictive control for coke oven blowing cooler system based on support vector regression
摘要
Abstract
Coke oven blowing cooler system is difficult to establish accurate mathematical model for its strong nonlinearity.To solve the problem,a predictive control strategy based on support vector regression(SVR) is proposed.SVR based on the structural risk minimization can directly reflect model nonlinear characteristics,and the adaptive weight particle swarm optimization(APSO) is utilized to optimize the SVR identification parameters.The rolling of the finite horizon optimization and the feedback correction of can predictive control which is the main body of the control system,overcome the uncertainty and nonlinear process effectively.On the MATLAB simulation platform,this control strategy is compared with the traditional PID (proportion integration differention).The simulation results show that the control strategy has strong anti-interference and robustness,which ensures the rapid and effective stability of the pre-cooling device in the process.关键词
焦炉冷鼓系统/支持向量回归机/预测控制/鲁棒性/传统PIDKey words
coke oven blowing cooler system/support vector regression/predictive control/robustness/traditional PID分类
信息技术与安全科学引用本文复制引用
张世峰,程曾婉,陈威,李泉..基于SVR的焦炉冷鼓系统预测控制[J].重庆大学学报,2017,40(9):76-82,7.基金项目
安徽省教育厅自然科学研究项目(KJ2008B104) （KJ2008B104）
安徽工业大学2016年研究生创新基金资助项目(2016033).Supported by Anhui Prorincial Department of Education Natural Science Research Projrct (KJ2008B104) （2016033）
Anhui University of Technology 2016 Graduate Innovation Research Fund Poject(2016033). （2016033）
