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冷轧板形多变量模型预测控制

Multivariable model predictive control of cold rolled strip shape

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冷轧板形是带钢冷轧过程中重要的质量指标之一,板形控制是冷轧过程中的核心技术.为了实现高精度、高效率的板形控制,提出了基于动态矩阵控制(dynamic matrix control,DMC)算法的冷轧板形多变量模型预测控制的方法.为了充分验证预测模型调控效果,首先分别利用偏最小二乘法(partial least squares,PLS)和主成分分析法(principal component analysis,PCA)计算获取两套板形调控功效系数并进行了准确性验证;然后建立了基于DMC算法的板形调控模型;最后模拟在一套轧机上输入以PLS计算获得的准确调控功效系数模拟模型匹配情况,并将两条板形偏差曲线导入到分别基于DMC算法、最优控制算法和遗传算法(genetic al-gorithm,GA)建立的预测模型中进行优化.同样,输入以PCA计算获得的不准确调控功效系数模拟模型失配情况,将两条偏差曲线导入到3个预测模型中进行优化.基于以上条件,得到基于DMC算法的预测模型在模型匹配时标准差分别为0.63 I和0.25 I,模型失配时标准差分别为2.20I和1.81I,调节时间约为100 ms.结果表明,无论在模型匹配还是失配情况下DMC算法对于冷轧板形均具有良好的调控效果.
The shape of cold rolled strip is one of the important quality indexes in the cold rolling process of strip steel,and the shape control is the core technology in the cold rolling process.In order to achieve high-precision and high-efficiency shape control,a multivariable model predictive control method based on dynamic matrix control algorithm for cold-rolled strip shape was proposed.In order to fully verify the control effect of the prediction model,two sets of shape control efficiency coeffi-cients were calculated using partial least squares method and principal component analysis method,respectively,and their accuracy was verified.Then,a shape control model based on dynamic matrix control algorithm was established.Finally,the simulation was conducted on a set of rolling mills,and the accurate control efficiency coefficient obtained by partial least squares method was input to simu-late the model matching.Two shape deviation curves were imported into the prediction models estab-lished based on dynamic matrix control algorithm,optimal control algorithm,and genetic algorithm for optimization.Similarly,the inaccurate control efficiency coefficients calculated using principal compo-nent analysis were input to simulate model mismatch,and two deviation curves were imported into three prediction models for optimization.Based on the above conditions,the prediction model based on dynamic matrix control algorithm has standard deviations of 0.63 I and 0.25 I during model matc-hing,2.20 I and 1.811 during model mismatch,and the adjustment time is about 100 ms.The results show that the dynamic matrix control algorithm has a good control effect on the shape of cold rolled strip,whether in the case of model match or mismatch.

cold rolled strip shapedynamic matrix control algorithmpredictive controlefficiency co-efficient of shape control

张文雪、齐东旭、崔健

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上海宝信软件股份有限公司自动化事业本部,上海 201900

东北大学轧制技术及连轧自动化国家重点实验室,辽宁沈阳 110819

山东钢铁集团日照有限公司钢铁研究院,山东日照 276800

冷轧板形 动态矩阵控制算法 预测控制 板形调控功效系数

国家重点研发计划项目国家自然科学基金国家自然科学基金国家自然科学基金辽宁省兴辽英才计划项目中央高校基本科研业务费资助项目

2022YFB3304800U21A20117U21A2047552074085XLYC1907065N2004010

2023

10.3969/j.issn.1000-7059.2023.05.012

冶金自动化
冶金自动化研究设计院

冶金自动化

影响因子：0.685
ISSN：1000-7059
年,卷(期)：2023.47(5)
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