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塑料工业中最小方差基准的控制系统性能评价 被引量:1

Evaluation of Minimum Variance Benchmark of Control System Performance in Plastic Industry
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摘要 伴随着我国塑料制造产业产量的增大和自动化水平的上升,亟需精确性更高的控制系统性能评价方式对其生产系统运行数据进行评价,以提高产品生产效率和质量。以塑料工业生产典型的单输入/输出系统过程控制为研究对象,分别对其数据检验和预处理方式进行介绍。基于实际运行数据和时间延迟信息,提出无信号干扰状态下最小方差基数的控制系统性能评价方法。并以实际生产中可能存在的不同类型干扰信号为例,分析干扰信号模型,提出对其进行平稳化处理的方法。 As the increasing in the production of plastic industry and the improving in the automauon in China, the evaluation method with greater precision for a control system performance is required to evaluate operation data production of operation system, in order to improve the production efficiency and product quality. Based on typical process control of a single input/output system for plastic industrial production as the research object, this paper introduced the mode of data validation and data pretreatment. Based on the actual operation data and time delay information, we proposed a evaluation method for the minimum variance benchmark of control system performance without signal interference. With different types of jamming signal in the actual production as examples, the interference signal model was analyzed and its smooth processing method was put forward.
作者 聂晓音
出处 《塑料工业》 CAS CSCD 北大核心 2016年第12期145-148,共4页 China Plastics Industry
关键词 塑料工业 最小方差基准 时间序列 单输入/输出系统 非平稳信号 Plastics Industry Minimum Variance Benchmark Time Series Single Input/OutputSystem Non-stationary Signal
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  • 1张兴会,刘玲,陈增强,袁著祉,.应用Elman神经网络的混沌时间序列预测[J].华东理工大学学报(社会科学版),2002,17(S1):30-33. 被引量:9
  • 2王珏,秦伟良,钱海荣.上海股市的时间序列模型研究[J].统计与决策,2004,20(11):11-11. 被引量:5
  • 3席裕庚,王凡.非线性系统预测控制的多模型方法[J].自动化学报,1996,22(4):456-461. 被引量:61
  • 4MilIs T C.金融时间序列的经济计量学模型[M].北京:经济科学出版社,2002:217-355.
  • 5Weigend A S. Time Series Analysis and Prediction[D]. Colorado: Univerisity of Colorado, 1994.
  • 6Faloutsos C, Rangsnathan M, Manoloppoulos Y. Fast stubsequence matching in time - series databases[ C]//In. SIGMOD Proceedings of Annual Conference. Minneapolis: [ s. n. ], 1994:419- 429.
  • 7Xia B B. Similarity search in time series data set[D]. Canada: Simon Fraser University, 1997.
  • 8佚名.GARCH模型对沪市行业指数的实证研究[EB/OL].2008-10-12.http://www.govyi.com/lunwen/2008/200810/262942.shtml.
  • 9Ljung L. System identification: theory for the user[M]. 2nd ed. New York: Prentice-Hall, 1999.
  • 10Zhu Y C. Multivariable and closed-loop identification for MPC: the asymptotic method and its application[J]. Journal of Process Control, 1998, 8(2) : 101-115.

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