摘要
蒸馏塔工业控制过程的优化,是提高工业生产过程的关键。在评价蒸馏塔效能的过程中,由于其自由度、复杂性,使得蒸馏塔的液位控制过程的目标函数标准不统一。采用传统的精馏塔工业控制过程中,为了实现控制标准的统一,需要建立复杂的关联规则,导致约束条件过多,控制时效性降低。提出了利用层次分析法(AHP)和BP神经网络结合的工业控制过程优化方法。通过专家调查的方式获取显式和隐式评价指标值,在给出的评价模型和算法上,引入BP神经网络特征完成系统初始化,在经过在线评价,获得的最终评价分值,实现对蒸馏塔工业控制的优化,为操作人员的选择提供了有效的依据。
Optimization of the industrial control process of distillation column is the key to improve the industrial production process.In the process of evaluating the distillation column efficiency,because of its degrees of freedom and complexity,the standard of objective function in the liquid level control process of distillation column is not unified.In the process of using traditional industrial control of distillation column,in order to achieve the unification of the control standard,it needs to build complex association rules,leading to excess constraints,and lower timeliness of control.An optimization method for industrial control process based on the combination of analytic hierarchy process（AHP） and BP neural network is proposed.By means of the way of expert investigation,explicit and implicit evaluation indexes can be obtained,in the given evaluation model and algorithm,BP neural network features are introduced to complete system initialization.Then,after the online evaluation,the final evaluation score is obtained,so as to realize the optimization of industrial control of distillation column,providing effective evidence for the selection of operating personnel.
出处
《计算机仿真》
CSCD
北大核心
2016年第5期348-352,共5页
Computer Simulation
关键词
控制过程
蒸馏塔
性能评价
Control process
Distillation column
Performance evaluation
