CIESC Journal ›› 2018, Vol. 69 ›› Issue (S1): 87-94.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

LUO Lin, YANG Bo, LI Hongguang   

  1. College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China
  • Received:2018-03-08 Revised:2018-05-10 Online:2018-09-30 Published:2018-06-06

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.

Key words: dynamic multi-attribute decision making, control performance assessment, aging system, data integration

CLC Number: 

  • TP277

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