耿延兵. 基于模型预测控制算法的智能密度控制系统在选煤厂的应用[J]. 选煤技术, 2022, 50(2): 86-90. DOI: 10.16447/j.cnki.cpt.2022.02.017
    引用本文: 耿延兵. 基于模型预测控制算法的智能密度控制系统在选煤厂的应用[J]. 选煤技术, 2022, 50(2): 86-90. DOI: 10.16447/j.cnki.cpt.2022.02.017
    GENG Yanbing. Application of the intelligent density control system based on model predictive control algorithm in coal preparation plant[J]. Coal Preparation Technology, 2022, 50(2): 86-90. DOI: 10.16447/j.cnki.cpt.2022.02.017
    Citation: GENG Yanbing. Application of the intelligent density control system based on model predictive control algorithm in coal preparation plant[J]. Coal Preparation Technology, 2022, 50(2): 86-90. DOI: 10.16447/j.cnki.cpt.2022.02.017

    基于模型预测控制算法的智能密度控制系统在选煤厂的应用

    Application of the intelligent density control system based on model predictive control algorithm in coal preparation plant

    • 摘要: 为解决三河口选煤厂重介质旋流器分选过程中PID控制对合格介质密度控制调节能力有限等问题,采用系统辨识构建合格介质密度与精煤灰分数学模型,建立了基于模型预测控制(MPC)算法的智能密度控制系统,提高了合格介质密度控制精度,改善了重介质旋流器分选效果。现场应用表明:该系统在合格介质密度控制中应用效果良好,有效抑制了重介质选煤环节随机性干扰,实现了合格介质密度的稳定、动态调节,使精煤质量得到了显著提高,大大降低了精煤灰分波动幅度,稳定了产品质量,提高了经济效益。

       

      Abstract: The problem faced by Sanhekou Coal Preparation Plant is that the PID-controlled system for control and adjustment of the correct medium density in the process of coal cleaning using heavy medium cyclone is limited in capacity. To tackle this problem, a system identification-based mathematical model is developed based on historical correct medium density and clean coal ash data.The density of correct medium can be dynamically adjusted using the sophisticated model predictive control algorithm for improving density control accuracy and hence the efficiency of H. M. cyclone. Practice shows that the use of the method can yield a remarkable density control result and lead to effective restraining of random interference in heavy medium separation process, and stability of density of correct medium. Moreover, the ability of making dynamic density adjustment makes it possible to make noticeable upgrading of clean coal, drastically reduce fluctuation of clean coal ash and improve economic performance.

       

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