首页 | 本学科首页   官方微博 | 高级检索  
     

基于大滞后磨矿分级系统的动态分支预测转移控制技术
引用本文:王云峰,李战明,袁占亭,万维汉. 基于大滞后磨矿分级系统的动态分支预测转移控制技术[J]. 湖北大学学报(自然科学版), 2010, 32(2): 157-160
作者姓名:王云峰  李战明  袁占亭  万维汉
作者单位:王云峰,WANG Yunfeng(兰州理工大学,电气工程和信息工程学院,甘肃,兰州,730000;甘肃政法学院,计算机科学学院,甘肃,兰州,730070);李战明,袁占亭,LI Zhanming,YUAN Zhanting(兰州理工大学,电气工程和信息工程学院,甘肃,兰州,730000);万维汉,WAN Weihan(金川集团,自动化工程有限公司,甘肃,金昌,737104) 
基金项目:国家高技术产业发展计划项目,甘肃政法学院科研资助重点项目 
摘    要:针对较难控制的大滞后过程对象,提出动态分支预测转移控制技术,使控制回路在运行过程中始终保持最佳运行状态,最终提高工业过程设备的运行效率.通过在控制过程中增加对被控对象输入输出之间相关性的跟踪及处理,在基本预测控制算法的基础上再增加一个预测控制变量协调决策层,可在线任意拟合,利用反馈校正的滚动优化策略进行记录及优化,获得被控对象输入输出之间相关性及相应控制策略的动态分支预测转移控制表,结合系统设定值进行区间控制和约束保护措施,在暂态响应和稳态性能之间取得折衷,使控制效果得到明显的改善,不但增强输入控制量的规律性,而且提高响应的快速性和准确性.仿真实验表明模型的在线辨识精确,可以保证系统的鲁棒性能和预期的控制性能.

关 键 词:大滞后对象  动态分支预测转移控制  协调决策层  控制策略转移历史表  磨矿分级系统

Control technology research on predicting dynamic branches based on grinding and classification system with long time delay
WANG Yunfeng,LI Zhanming,YUAN Zhanting,WAN Weihan. Control technology research on predicting dynamic branches based on grinding and classification system with long time delay[J]. Journal of Hubei University(Natural Science Edition), 2010, 32(2): 157-160
Authors:WANG Yunfeng  LI Zhanming  YUAN Zhanting  WAN Weihan
Affiliation:1.College of electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730000,China;2.School of Information Science and Technology,Gansu Political Science and Law Institute,Lanzhou 730070,China;3.Jinchuan Group Ltd.,Automation Engineering Ltd.,Jinchang 737104,China)
Abstract:A control technology on predicting dynamic branches for large dead-time processes was put forward to keep the control loops being optimal all time and improved efficiency of process equipments as well,by the coordination and decision level of prediction control variables,a form on predicting dynamic branches was formed by treatment of relevance of input and output on controlled objects in control software and optimal tracing of rolling optimal strategy based on feedback correction,the technology made compromise between transient response and steady state performance.It is shown that the control effect was improved after field practical application.The technology not only emphasized regularity of input controlled variables,but also improved the accuracy and fast of the response.Simulation example showed that the online identified model was accurate and it could guarantee both desired robustness and control performance.
Keywords:large dead-time process  predicting dynamic branches  coordination and decision level  branch history table of control strategy  grinding and classification system
本文献已被 CNKI 维普 万方数据 等数据库收录!
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