Dynamic soft sensor modeling based on state detection and impulses response template

doi:10.1109/CCDC.2014.6852886

CORC > 兰州理工大学 > 兰州理工大学

	Dynamic soft sensor modeling based on state detection and impulses response template
	Fan, Zhi 1; Cao, Jie 1; Wei, Yujie 2
	2014
会议日期	May 31, 2014 - June 2, 2014
会议地点	Changsha, China
关键词	Forecasting Mass transfer Optimal control systems Particle swarm optimization (PSO) Accurate prediction Dynamic soft sensor Impulses Response Template Melt mass flow rates Prediction accuracy Soft sensors State Detection Swarm optimization algorithms
DOI	10.1109/CCDC.2014.6852886
页码	4031-4037
英文摘要	Accurate and reliable prediction of melt mass flow rate is crucial in polypropylene production. In order to establish an accurate prediction model, a process state detection method and a novel dynamic modeling method is proposed, and the model parameters are indentified by improved swarm optimization algorithm. A polypropylene product melt mass flow rate soft sensor model is established based on process state detection and impulses response template. According to the research on the data from real plant, the experiments demonstrate that even under dynamic state, the proposed approach can improve the prediction accuracy, and the soft sensor model has good tracking ability and meets the requirement of on-line optimal control. © 2014 IEEE.
会议录	26th Chinese Control and Decision Conference, CCDC 2014
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117681]
专题	兰州理工大学
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; 2.Departments of Automation, Tsinghua University, Beijing 100084, China
推荐引用方式 GB/T 7714	Fan, Zhi,Cao, Jie,Wei, Yujie. Dynamic soft sensor modeling based on state detection and impulses response template[C]. 见:. Changsha, China. May 31, 2014 - June 2, 2014.