Please wait a minute...
J4  2013, Vol. 47 Issue (7): 1253-1257    DOI: 10.3785/j.issn.1008-973X.2013.07.018
通信工程、自动化技术     
基于软测量技术的化工过程优化控制策略
叶凌箭,马修水
浙江大学宁波理工学院 信息科学与工程学院,浙江 宁波 315100
Optimal control strategy for chemical processes
based on soft-sensoring technique
YE Ling-jian, MA Xiu-shui
School of Information Science and Engineering, Ningbo Institute of Technology, Zhejiang
University, Ningbo 315100, China 
 全文: PDF  HTML
摘要:

针对参数不确定型系统,提出基于软测量技术的新优化控制思路.通过求解连续静态过程的优化模型,实时跟踪一阶最优性必要条件实现不确定系统的在线优化.借助软测量技术找到可测变量与不可测最优性必要条件之间的估计模型,以该模型的输出为被控变量直接实现过程的优化控制.与传统的实时优化(RTO)方法相比,新策略更加迅速有效,可用简单的控制器(如PID)实现.对一个蒸发过程的研究结果表明了该方法的有效性.

Abstract:

A new optimal control strategy was proposed based on soft-sensoring technique for parametricuncertain systems. By solving optimization problems for continuous processes, online optimal control was achieved  by tracking necessary conditions of optimality (NCO). Soft-sensoring technique was introduced to model the relationships between the measurements and unmeasured NCO. Then the outputs of the soft-sensoring models were used as the controlled variables to directly achieve optimality. New strategy is faster and more effective compared with traditional real-time optimization (RTO).  The method can be realized by using simple controllers (e.g. PID). An evaporator example was analyzed to illustrate the effectiveness of the strategy.

出版日期: 2013-07-01
:  TP 273  
基金资助:

浙江省自然科学基金资助项目(LQ13F030007, Y1101154);国家“973”重点基础研究发展规划资助项目(2012CB720505); 宁波市创新团队资助项目(2012B82002).

通讯作者: 马修水,男,教授.     E-mail: mxsh63@yahoo.com.cn
作者简介: 叶凌箭(1984-),男,讲师,从事厂级过程控制、控制结构设计的研究. E-mail: ljye@nit.zju.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

叶凌箭,马修水. 基于软测量技术的化工过程优化控制策略[J]. J4, 2013, 47(7): 1253-1257.

YE Ling-jian, MA Xiu-shui. Optimal control strategy for chemical processes
based on soft-sensoring technique. J4, 2013, 47(7): 1253-1257.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2013.07.018        http://www.zjujournals.com/eng/CN/Y2013/V47/I7/1253

[1]  ENGELL S. Feedback control for optimal process operation [J]. Journal of Process Control, 2007, 17(3): 203-219.
[2]  SRINIVASAN B, BONVIN D, VISSER E, et al. Dynamic optimization of batch processes - II. role of measurements in handling uncertainty [J]. Computers and Chemical Engineering, 2003, 27(1): 27-44.
[3]  FRANCOIS G, SRINIVASAN B, BONVIN D. Use of measurements for enforcing the necessary conditions of optimality in the presence of constraints and uncertainty [J]. Journal of Process Control, 2005, 15(6): 701-712.
[4]  CHACHUAT B, MARCHETTI A, BONVIN D. Process optimization via constraints adaptation [J]. Journal of Process Control, 2008, 18(3/4): 244-257.
[5]  MARCHETTI A, CHACHUAT B, BONVIN D. Modifier-adaptation methodology for real-time optimization [J]. Industrial and Engineering Chemistry Research, 2009, 48(13): 6022-6033.
[6]  FORTUNA L, GRAZIANI S, RIZZO A, et al. Soft sensors for monitoring and control of industrial processes [M]. London: Springer-Verlag, 2007.
[7]  EDGAR T F, HIMMELBLAU D M, LASDON L S. Optimization of chemical processes [M]. 2nd ed. [S.l.]: McGraw-Hill, 2001.
[8]  CHACHUAT B, SRINIVASAN B, BONVIN D. Adaptation strategies for real-time optimization [J]. Computers and Chemical Engineering, 2009, 33(10):1557-1567.
[9]  SRINIVASAN B, BIEGLER L T, BONVIN D. Tracking the necessary conditions of optimality with changing set of active constraints using a barrier-penalty function [J]. Computers and Chemical Engineering, 2008, 32(3): 572-579.
[10]  NEWELL R B, LEE P. Applied process control: a case study [M]. New York, Sydney : Prentice-Hall of Australia, 1989.
[11]  CAO Y. Direct and indirect gradient control for static optimisation [J]. International Journal of Automation and Computing, 2005, 2(1): 1555-1564.

[1] 程森林,李雷,朱保卫,柴毅. WSN定位中的RSSI概率质心计算方法[J]. J4, 2014, 48(1): 100-104.
[2] 方强, 陈利鹏, 费少华, 梁青霄, 李卫平, 赵金锋. 定位器模型参考自适应控制系统设计[J]. J4, 2013, 47(12): 2234-2242.
[3] 罗继亮, 王飞,邵辉,赵良煦. 基于约束转换的Petri网最优监控器设计[J]. J4, 2013, 47(11): 2051-2056.
[4] 李奇安, 金鑫. 对角CARIMA模型多变量广义预测近似解耦控制[J]. J4, 2013, 47(10): 1764-1769.
[5] 任雯, 胥布工. 基于FI-SNAPID算法的经编机多速电子送经系统开发[J]. J4, 2013, 47(10): 1712-1721.
[6] 叶凌云,陈波,张建,宋开臣. 基于最少拍无波纹算法的高精度动态标准源反馈控制[J]. J4, 2013, 47(9): 1554-1558.
[7] 孟德远,陶国良,钱鹏飞,班伟. 气动力伺服系统的自适应鲁棒控制[J]. J4, 2013, 47(9): 1611-1619.
[8] 黄晓烁,何衍,蒋静坪. 基于互联网无刷直流电机传动系统的控制策略[J]. J4, 2013, 47(5): 831-836.
[9] 贺乃宝, 高倩, 徐启华, 姜长生. 基于自适应观测器的飞行器抗干扰控制[J]. J4, 2013, 47(4): 650-655.
[10] 朱予辰,冯冬芹,褚健. 基于EPA的块数据流通信调度与控制[J]. J4, 2012, 46(11): 2097-2102.
[11] 刘志鹏, 颜文俊. 预粉磨系统的智能建模与复合控制[J]. J4, 2012, 46(8): 1506-1511.
[12] 朱康武, 顾临怡, 马新军, 胥本涛. 水下运载器多变量鲁棒输出反馈控制方法[J]. J4, 2012, 46(8): 1397-1406.
[13] 费少华,方强,孟祥磊,柯映林. 基于压脚位移补偿的机器人制孔锪窝深度控制[J]. J4, 2012, 46(7): 1157-1161.
[14] 于晓明, 蒋静坪. 基于神经网络延时预测的自适应网络控制系统[J]. J4, 2012, 46(2): 194-198.
[15] 罗莉华, 龚李龙, 李平, 王慧. 考虑驾驶员行驶特性的双模式自适应
巡航控制设计
[J]. J4, 2011, 45(12): 2073-2078.