基于广义预测控制的松散回潮出口含水率控制系统

松散回潮作为卷烟生产加工的首道核心工序，其出口含水率稳定性对后续各工序工艺指标有着直接的影响。为解决松散回潮工序烟片出口含水率控制精度低、过程控制能力弱等问题，本文围绕德国虹霓TB-L（flex）松散回潮机控制系统进行优化升级，充分利用厂内现有的工业控制和信息化系统采集制丝实时数据并分析，而后采用广义预测控制（generalized predictive control，GPC）方法，建立了具备工况自适应能力的加水量动态预测和调整模型，并编写相应的软件模块对过程进行自动化控制，实现了工艺过程参数动态优化、智能化的预测性控制系统。实际应用效果表明，该系统有效提高了松散回潮工序出口含水率稳定性。

Control System for Moisture Content in Output Strips of Loosening and ConditioningProcess Based on Generalized Predictive Control

The loosening and conditioning process is at the beginning of a tobacco manufacturing line, and thus the quality of the following processes depends on the accuracy and stability of it. This work investigated on improving output moisture content stability by collecting and analyzing process data and then applying advanced control technologies to the process. Specifically, multi-dimensional process data was collected and analyzed using correlation and regression methods. A generalized predictive control (GPC) algorithm was then developed and applied to optimize the control of water flow rate in real time. Results of 133 batches of production under the new GPC method showed that CPK of output material moisture content increased by more than 50% after applying the new control method.