薄带材冷连轧非稳态耦合过程的在线感知与多机架动态协调优化

The unsteady state in tandem cold rolling for thin strip is characterized by the difficult accurately description of mathematical model, the cross coupling of all stands, and the complex and changeable constraints of rolling technology. Improving the stability of this process and the quality of products is the key to further enhance the control level of tandem cold rolling, and that improvement needed to be solved. The rolling technology and the advanced control theory should be deeply integrated to amend the accuracy of thin strip rolling model of unsteady state process model, and improve the adaptability of control strategy for complex and changeable conditions, and realize multi-stand coordinative optimization. The production data and rolling mechanism are combined to modify the key models (roll force, forward slip, etc.) in thin strip cold rolling, the stand state space model is established, and the model is online identified by closed-loop subspace identification method, the operating mechanism and influence law of the cross coupling of all stands are revealed. Expendable model library of equipment and technology constraints is built, objective functions is formulated by expressing of the constraint priority and the flexible range of process quality parameters to indicate the rolling state, the dynamic optimization method of rolling technology for unsteady state process in tandem cold rolling is researched. The thickness-tension predictive control subsystem of single stand is established, distributed coordinative optimization method of entire tandem cold rolling process is studied by developing the comprehensive control objective function of multi-stand. The research results will provide new ideas to improve production stability and thickness accuracy in tandem cold rolling unsteady state process for thin strip.

薄带材冷连轧的非稳态过程具有难以用机理模型准确描述、多机架交叉耦合、轧制工艺约束复杂多变等特征，如何提高该过程的稳定性和产品质量，是冷连轧控制水平进一步提升的关键和亟待解决的问题。为此，需要将轧制工艺与先进控制理论深度融合，改善薄带材非稳态轧制的模型精度，提高轧制工艺对复杂多变工况的适应能力，并实现多机架一体化协调控制。本项目融合生产数据和轧制机理修正薄带材冷轧轧制力、前滑等关键数学模型，建立机架状态空间模型并采用闭环子空间辨识法在线辨识，揭示多机架交叉耦合运行机制和影响规律；构建可拓展的工艺约束模型库，明确优先级和满意度系数，通过指标评价函数实时感知轧制运行状态，研究冷连轧非稳态过程轧制工艺的动态设定方法；构建单机架厚度-张力预测控制子系统，制定多机架综合控制目标函数，给出冷连轧全过程的分布式协调优化方法。研究成果可为薄带材冷连轧非稳态过程的生产稳定性提高和质量精度改善提供新的思路。

薄带材冷连轧的非稳态过程具有难以用机理模型准确描述、多机架交叉耦合、轧制工艺约束复杂多变等特征。本项目将轧制工艺与先进控制理论深度融合，改善了薄带材非稳态轧制的模型精度，提高了轧制工艺对复杂多变工况的适应能力，并实现了多机架一体化协调控制。.（1）推导了各机架轧制参数的增量方程，建立了基于厚度-张力的冷连轧状态空间模型。模拟了干扰量和控制量改变时，各机架出口带钢厚度和带钢张力的变化过程，动态分析了各轧制参数对轧制状态的影响规律；统计了各扰动量和输出量在最终平衡状态下的响应数据，分析了各轧制参数的变化规律。.（2）给出了一种基于粒子群算法优化支持向量机的轧辊辊缝预测策略，通过均方差误差和平均绝对误差等评价指标对比了预测策略的性能，改进的预测策略具有良好的模型预测性能和泛化能力。根据实际工况和轧制数据，回归出了基于轧制速度和带钢塑性系数的轧辊辊缝补偿模型，并验证了辊缝补偿模型的有效性。.（3）提出了一种冷轧多自由度水平-垂直-扭转轧机振动机理研究模型。基于动态轧制力与轧机结构模型，研究了因张力变化而引起的负阻尼效应，采用混合润滑理论分析了轧机振动摩擦系数稳定性区间出现的原因。通过将生产现场的轧制过程数据、轧机振动加速度数据和智能算法相结合，给出了一种基于数据驱动的轧机异常振动预警方法。.（4）基于冷连轧各机架关联的子系统模型，建立了子系统的预测控制器，结合邻域优化理论，充分考虑了邻域的性能指标，完成了厚度和张力系统的优化控制。研究结果表明，与其他控制器相比，DMPC控制器具有良好的跟踪性能和抗干扰性能，能够保持快速的在线优化；同时，DMPC控制器具有更快的计算速度，降低了控制系统的负载。.发表相关学术论文29篇，其中SCI收录22篇；申请发明专利7项，其中授权4项；登记软件著作权3项；培养博士研究生毕业3人，硕士研究生毕业5人；主编出版学术专著1部；获得省科技进步二等奖1项。