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基于案例推理的加料工序出口含水率自适应控制系统设计

王莹 杨义 张以宁 周成林 杨常勇 张胜利

烟草科技2026,Vol.59Issue(8):76-81,6.
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烟草科技2026,Vol.59Issue(8):76-81,6.DOI:10.16135/j.issn1002-0861.2025.0504

基于案例推理的加料工序出口含水率自适应控制系统设计

Design of a case-based reasoning adaptive control system for outlet moisture content in the tobacco casing process

王莹 1杨义 1张以宁 2周成林 2杨常勇 1张胜利3

作者信息

  • 1. 河南中烟工业有限责任公司黄金叶生产制造中心,郑州经济技术开发区第三大街9号 450000
  • 2. 首域科技(杭州)有限公司,杭州市滨江区六和路368号一幢(北)二楼D2044室 310051
  • 3. 河南中烟工业有限责任公司,郑州市管城回族区榆林南路16号 450000
  • 折叠

摘要

Abstract

To address the difficulty of maintaining stable outlet moisture control using conventional PID control in the casing process of tobacco primary processing where multivariable coupling and significant time lag are present,an intelligent control method based on case-based reasoning(CBR)was proposed.This method employs a three-level control architecture that integrates the clustering of historical operating conditions,real-time data matching,and dynamic parameter optimization.Firstly,historical production data was clustered to construct a multidimensional feature case base.Secondly,an improved dynamic optimization algorithm was used to match real-time operating conditions with historical cases and determine the optimal control input for the compensation steam valve opening.Finally,a closed-loop feedback mechanism was introduced to adaptively correct the valve opening according to the deviation between the actual and set-point values of outlet moisture content,thereby enabling dynamic optimization of the control parameters.Industrial validation was conducted using cigarette products with four specifications produced by Golden Leaf Production and Manufacturing Center.The results showed that the proposed method significantly improved the control performance of outlet moisture content in the casing process.The process capability index(Cpk)increased from 1.098-1.523 to 1.574-2.248,representing an improvement of 15.4%-65.7%,while the standard deviation of moisture content decreased by 3.4%-23.8%.The proposed method provides a practical approach for improving process stability and intelligent control in tobacco primary processing.

关键词

制丝工艺/加料工序/自适应控制/案例推理/自学习参数修正/出口含水率

Key words

Tobacco primary processing/Casing process/Adaptive control/Case-based reasoning/Self-learning parameter correction/Outlet moisture content

分类

轻工纺织

引用本文复制引用

王莹,杨义,张以宁,周成林,杨常勇,张胜利..基于案例推理的加料工序出口含水率自适应控制系统设计[J].烟草科技,2026,59(8):76-81,6.

基金项目

河南中烟工业有限责任公司科技项目"基于模型预测控制的叶丝加料工序参数优化研究"(AW202116). (AW202116)

烟草科技

1002-0861

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