A dynamic multi-attribute decision making approach to industrial process control performance evaluations

LUO Lin; YANG Bo; LI Hongguang

doi:10.11949/j.issn.0438-1157.20180259

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A dynamic multi-attribute decision making approach to industrial process control performance evaluations

更新时间：2025-12-10

- A dynamic multi-attribute decision making approach to industrial process control performance evaluations
- CIESC Journal Issue S1, Pages: 87-94(2018)
- 作者机构：
  
  北京化工大学信息科学与技术学院,北京,100029
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20180259
  CLC： P277
- Online First：30 September 2018，
  
  Published：30 September 2018
- 稿件说明：
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LUO Lin, YANG Bo, LI Hongguang. A dynamic multi-attribute decision making approach to industrial process control performance evaluations[J]. CIESC Journal, 2018, (S1): 87-94.
DOI：

LUO Lin, YANG Bo, LI Hongguang. A dynamic multi-attribute decision making approach to industrial process control performance evaluations[J]. CIESC Journal, 2018, (S1): 87-94. DOI： 10.11949/j.issn.0438-1157.20180259.

摘要

工业控制系统由于设备老化而导致控制性能发生变化，而传统的控制性能评价方法对于这种慢时变特性具有局限性。提出了一种基于变权动态多属性决策的控制性能评价方法。首先在对系统性能进行判断时，利用系统故障率与运行时间相结合的计算方法对系统的运行状态进行划分，获得不同运行阶段的决策信息；采用四个评价指标分别为超调量、非线性指标、输出方差、阀黏滞指标构造多属性决策判断矩阵，对老化慢时变系统进行评价，并运用色谱分析法计算决策过程中属性权重的变化，最终确定当前性能运行状态；将该方法应用于某工业DMF回收装置中，对比实验结果验证了该方法的有效性。

Abstract

Practically

the aging of industrial equipments could lead to varying performances of control systems

while traditional control performance evaluation methods show limitations in this scenario. In response

a control system performance adaptive evaluation approach based on variable weight dynamic multi-attribute decision-making is proposed. Firstly

to judge the control performance

a calculation method that combines the system failure rate and operating time is suggested to divide the operating state of control systems to ensure that the decision information comes from different operation stages. Subsequently

a multi-attribute decision-making matrix is constructed with four evaluation indicators including the overshoot

nonlinear index

output variance

and valve stick index to evaluate aging slow time-varying systems. An analytic hierarchy process method is used to calculate the change of the attribute weight in the decision process to determine the current performance state. The proposed method was applied to an industrial DMF recovery plant

demonstrating the effectiveness of the method.

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