引用本文:徐正光,王目树,郭玲利.基于模式运动的一类生产过程调节性能与聚类参数关系[J].控制与决策,2020,35(5):1025-1038
【打印本页】   【HTML】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】 附件
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览次   下载 本文二维码信息
码上扫一扫!
分享到: 微信 更多
基于模式运动的一类生产过程调节性能与聚类参数关系
徐正光,王目树, 郭玲利
(北京科技大学自动化学院,北京100083)
摘要:
为研究基于模式运动的系统动力学描述方法中聚类参数对生产过程调节性能的影响,给出描述系统动态调节性能与产品质量调节性能的指标,分析并建立了聚类参数与系统调节性能间的关系;介绍了基于模式运动的一类复杂生产过程建模方法,并利用LMI方法给出了状态反馈控制器设计方法;提出了基于粒子群优化方法的最大熵聚类算法,定义并提取了系统调节性能指标;利用提出的新的覆盖分类神经网络,建立最大熵聚类方法的参数与调节性能间的映射关系,并分析了分类网络泛化能力;采用实际烧结矿生产数据进行仿真,结果表明所提方法可以分析与建立调节性能与聚类参数间的关系,且可为实际生产中聚类参数的选择提供一定的依据.
关键词:  模式运动  调节性能  神经网络  模式聚类  模式识别  过程控制
DOI:10.13195/j.kzyjc.2018.1142
分类号:TP273
基金项目:
Relationship between clustering parameters and regulation performance of a class of production processes based on pattern moving
XU Zheng-guang,WANG Mu-shu,GUO Ling-li
(School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing100083,China)
Abstract:
In order to study the influence of clustering parameters on the regulation performance of production processes in the pattern-moving-based system dynamics description method, indexes describing dynamic regulation performance and product quality regulation performance are proposed, and the relationship between clustering parameters and regulation performance is analyzed and built. A pattern moving based modeling method of a class of production processes is introduced. A state feedback controller is designed by using the LMI method. A maximum-entropy clustering algorithm based on the particle swarm optimization(PSO) is proposed, and regulation performance of process control is defined and extracted. The relationship between clustering parameters and regulation performance is built by using a proposed classification neural network based on a covering algorithms, and generalization of the network is analyzed. Data of an actual sintering process is used for simulation experiments, and results demonstrate that the proposed method can be used to analyze and build the relationship between clustering parameters and regulation performance, which provides a basis for the selection of clustering parameters in actual production.
Key words:  pattern moving  regulation performance  neural network  pattern clustering  pattern recognition  process control

用微信扫一扫

用微信扫一扫