Operational Optimization and Feedback Control for Complex Industrial Processes
Operational Optimization and Feedback Control for Complex Industrial Processes
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DOI：
10.3724/sp.j.1004.2013.01744
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
C. Tian
中科院分区：
文献类型：
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作者：
C. Tian
过程控制不仅要保证被控变量遵循设定值，还要保证整个过程装置最优地满足运行要求(如：（质量、效率和消耗）。过程控制还应使质量和效率的操作指标不断得到改进，同时使与消耗有关的指标保持在尽可能低的水平。本文在综述现有运行优化和控制方法的基础上，针对难以获得过程运行模型的复杂工业过程，提出了一种数据驱动的混合智能最优运行控制方法。通过混合仿真系统和赤铁矿选矿工业磨矿过程的应用，验证了所提出的操作控制方法的有效性。在本文结束之前，概述了复杂工业过程最优运行控制的未来研究问题。
Process control should ensure not only controlled variables to follow their setpoint values, but also the whole process plant to meet operational requirements optimally(e.g., quality, efciency and consumptions). Process control should also enable operational indices for quality to and efciency to be improved continuously, while keeping the indices related to consumptions at the lowest possible level. This paper starts with a survey on the existing operational optimization and control methodologies and then presents a data-driven hybrid intelligent optimal operational control for complex industrial processes where process operational models are difcult to obtain. Applications via a hybrid simulation system and an industrial grinding process for hematite ore mineral processing are presented to demonstrate the efectiveness of the proposed operational control method. Issues for future research on the optimal operational control for complex industrial processes are outlined before concluding the paper.