Please wait a minute...
J4  2010, Vol. 44 Issue (8): 1460-1465    DOI: 10.3785/j.issn.1008-973X.2010.08.005
自动化技术     
控制回路性能评价方法及在PTA生产装置的应用
陈绍绵,赵均,李华银,钱积新
浙江大学 工业控制国家重点实验室,浙江 杭州 310027
Control loop performance assessment method with applications in
PTA production equipment
CHEN Shao-mian, ZHAO Jun, LI Hua-yin, QIAN Ji-xin
State Key Laboratory of Industrial Control Technology, Hangzhou 310027, China
 全文: PDF  HTML
摘要:

针对工业现场扰动具有噪声大、易频发、时变的特点,将遗忘因子引入到控制回路性能评价的辨识过程中,提出一种改进的基于最小方差准则的性能评价方法.与传统的方法相比,带遗忘因子的辨识方法不仅能够考虑历史数据的影响,而且能够突出新数据提供的信息量.通过引入遗忘因子参数,能够防止数据饱和,并提高在工业过程时变扰动下控制性能评估的准确性和稳定性.该方法在仿真实验和工业PTA生产应用中得到了论证,结果表明,该方法能够为工业控制回路提供一个准确的性能评价指标,有效指导操作人员对潜在的问题回路进行优化调整,实现生产的平稳运行.

Abstract:

As the noise in industrial processes have remarkable amplitude, frequent happening and timevariant characteristics, an improved performance assessment method based on minimum variance control (MVC) benchmark was presented, in which forgetting factor was introduced to identification process for the performance assessment of control loops. Compared with the traditional approach, the identification method with forgetting factor could not only consider the influence of historical data, but also emphasize the information included in the new data. Through introducing the forgetting factor parameters, data saturation was prevented and the accuracy and stability of control performance assessment was improved in the industrial process with timevariant disturbance. The proposed method was demonstrated by the simulation and industrial PTA process application. The results showed that the method can provide an accurate performance assessment index for industrial control loop, effectually guide the operators to optimize and retune the underlying loops that have potential performance problem, and stabilize the process operation.Key words: performance assessment; PID controller; minimum variance control; timevariant disturbance; forgetting factor

出版日期: 2010-09-21
:  TP 273  
基金资助:

国家自然科学基金资助项目(60804023),国家“863”高技术研究发展计划资助项目(2007AA041402),国家“十一五”科技支撑计划资助项目(2007BAF22B05).

作者简介: 陈绍绵(1982-),男,浙江苍南人,博士生,从事预测控制、性能监控和故障诊断的研究.E-mail: smchen@iipc.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:

陈绍绵, 赵均, 李华银, 钱积新. 控制回路性能评价方法及在PTA生产装置的应用[J]. J4, 2010, 44(8): 1460-1465.

CHEN Chao-Mian, DIAO Jun, LI Hua-Yin, JIAN Ji-Xin. Control loop performance assessment method with applications in
PTA production equipment. J4, 2010, 44(8): 1460-1465.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2010.08.005        http://www.zjujournals.com/eng/CN/Y2010/V44/I8/1460

[1] ASTROM K J, HAGGLUND T. PID controllers: theory, design, and tuning [M]. 2nd ed.  New York: ISA 1995: 5970.
[2] BIALKOWSKI W L. Dreams vs. reality: a view from both sides of the gap [J]. Pulp and Paper Canada, 1993, 94(11): 1927.
[3] MITCHELL W, SHOOK D, SHAH S L. A picture worth a thousand control loops: an innovative way of visualizing controller performance data [C]∥ Control Systems Conference. Quebec City: [s. n.], 2004: 147158.
[4] HAGGLUND T. Industrial implementation of online performance monitoring tools [J]. Control Engineering Practice, 2005, 13(11): 13831390.
[5] INGIMUNDARSON A, HAGGLUND T. Closedloop performance monitoring using loop tuning [J]. Journal of Process Control, 2005, 15(2): 127133.
[6] LYNCH C B, DUMONT G A. Control loop performance monitoring [J]. IEEE Transactions on Control Systems Technology, 1996, 4(2): 185192.
[7] KOZUB D J. Controller performance monitoring and diagnosis: experiences and challenges [C]∥ Proceedings of the 5th International Conference on Chemical Process Control. Tahoe: AIChE and CACHE, 1996: 8396.
[8] VISHNUBHOTLA A, SHAH S L, HUANG B A. Feedback and feedforward performance analysis of the Shell industrial closed loop data set [C]∥ IFAC Symposium Advanced Control of Chemical Processes. Banff Alberta: Pergamon Press Oxford, 1997: 313318.
[9] THORNHILL N F, OETTINGER M, FEDENCZUK P. Refinerywide control loop performance assessment [J]. Journal of Process Control, 1999, 9(2): 109124.
[10] THORNHILL N F, OETTINGER M, FEDENCZUK P. Performance assessment and diagnosis of refinery control loops [J]. AIChE Symposium Series, 1998, 94(320): 373379.
[11] YUAN Q L, LENNOX B. Control performance assessment for multivariable systems based on a modified relative variance technique [J]. Journal of Process Control, 2009, 19(3): 489497.
[12] XU F W, HUANG B, TAMAYO E C. Performance assessment of MIMO control systems with timevariant disturbance dynamics [J]. Computers and Chemical Engineering, 2008, 32(9): 21442154.
[13] QIN S J. Control performance monitoring: a review and assessment [J]. Computer and Chemical Engineering, 1998, 23(2):173186.
[14] HARRIS T J, SEPPALA C T. DESBOROUGH L. A review of performance monitoring and assessment techniques for univariate and multivariate control systems [J]. Journal of Process Control, 1999, 9(1): 117.
[15] DESBOROUGH L, HARRIS T. Performance and assessment measures for univariate feedback control [J]. Canadian Journal of Chemical Engineering, 1992, 70(6): 11861197.
[16] HAN Kai, ZHAO Jun, XU Zhuhua, et al. A closedloop particle swarm optimizer for multivariable process cntrollers design [J]. Journal of Zhejiang University:Science A, 2008, 9(8): 10501060.

[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] 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.
[5] 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.
[6] 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.
[7] 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.
[8] 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.
[9] 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.
[10] 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.
[11] 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.
[12] 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.
[13] 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.
[14] 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.
[15] 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.