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Product quality adaptive control system for a food extruder.

机译：用于食品挤出机的产品质量自适应控制系统。

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摘要

Automatic twin screw extruder (TSE) control was implemented comparing both fixed and adaptive controllers on an APV-MPF50 TSE. Product quality attributes (PQA) were controlled using MIMO and MISO based GPC algorithms. Vision system parameters along with sensory data were correlated off-line with the PQA in search for potential control candidates. The initial system analysis and parameter correlations used steady state analysis of an RSM experimental design. Dynamic response analyses utilized both step response and pseudo random signal experiments. An on-line food-grade RTD method was illustrated using colorimetric technique.; Stochastic X, ARX, and ARMAX models were developed. Model predictive controllers were developed along GPC guidelines and extended to include combination GPC-SPC methods. Models and controllers were simulated using actual process noise and implemented on-line to compare performance. Tracking performance was compared using step changes in setpoints. The reaction to typical uncontrolled disturbances was also evaluated by using corn meal of different granulation and moisture content, barrel temperature setpoint changes, and simulating screw wear via die resistance change. In all cases, all controllers performed the desired control function. The combination of SPC and GPC control principles provided the smoothest responses to regulation and tracking requests by eliminating response to noise.; Adaptive control with open loop estimation improved performance slightly over the fixed ARX controller. The adaptive algorithm combined with SPC logic and supervisory logic offers the best alternative for automatic TSE extruder control.; Finally, an attempt to increase the degrees of freedom for control was researched on a second extruder (Wenger TX-52 TSE). A choke valve was introduced in the die neck to explore the relationship between total die resistance and PQA. In this set of experiments, the uncontrolled disturbance was screw wear (simulated by cone screw set back). The data indicated that valve adjustment could be used successfully for compensation of screw wear and as a fine tuning control option for adjustment of work input. In this part of the research, automatic control was not implemented since the valve used was manual.
机译：通过在APV-MPF50 TSE上比较固定控制器和自适应控制器，实现了自动双螺杆挤出机（TSE）控制。产品质量属性（PQA）使用基于MIMO和MISO的GP​​C算法进行控制。视觉系统参数以及感官数据与PQA离线关联，以寻找潜在的控制候选者。初始系统分析和参数相关性使用RSM实验设计的稳态分析。动态响应分析利用了阶跃响应和伪随机信号实验。用比色法说明了在线食品级RTD方法。开发了随机X，ARX和ARMAX模型。模型预测控制器是根据GPC指南开发的，并扩展到包括GPC-SPC组合方法。使用实际的过程噪声对模型和控制器进行仿真，并在线执行以比较性能。使用设定值的阶跃变化来比较跟踪性能。还通过使用不同粒度和水分含量的玉米粉，料筒温度设定值变化以及通过模头电阻变化模拟螺杆磨损来评估对典型不受控制干扰的反应。在所有情况下，所有控制器均执行所需的控制功能。 SPC和GPC控制原理的结合通过消除对噪声的响应，提供了对调节和跟踪请求的最平滑响应。具有开环估计的自适应控制比固定ARX控制器略微提高了性能。自适应算法结合了SPC逻辑和监控逻辑，为自动TSE挤出机控制提供了最佳选择。最后，在第二台挤出机（Wenger TX-52 TSE）上研究了增加控制自由度的尝试。在模颈中引入了一个节流阀，以研究总模阻与PQA之间的关系。在这组实验中，不受控制的干扰是螺钉磨损（通过锥形螺钉后退模拟）。数据表明，阀门调节可以成功地用于补偿螺杆磨损，并可以作为微调控制选项来调节工作输入。在这部分研究中，由于所使用的阀门是手动的，因此未实施自动控制。

著录项

  • 作者

    Schonauer, Sylvia Lynn.;

  • 作者单位

    Texas A&M University.;

  • 授予单位 Texas A&M University.;
  • 学科 Engineering Agricultural.; Agriculture Food Science and Technology.
  • 学位 Ph.D.
  • 年度 1995
  • 页码 333 p.
  • 总页数 333
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农业工程;农产品收获、加工及贮藏;
  • 关键词

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