Determining the state of a process control system: Current trends and future challenges

被引：59

作者：

Shardt, Y. ^{[1
]}

Zhao, Y. ^{[1
]}

Qi, F. ^{[1
]}

Lee, K. ^{[1
]}

Yu, X. ^{[1
]}

Huang, B. ^{[1
]}

Shah, S. ^{[1
]}

机构：

[1] Univ Alberta, Edmonton, AB T6G 2G6, Canada

来源：

CANADIAN JOURNAL OF CHEMICAL ENGINEERING | 2012年 / 90卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

performance assessment; minimum variance; LQG; plantwide; review; CONTROL PERFORMANCE ASSESSMENT; PLANT-WIDE OSCILLATIONS; PROCESS FAULT-DETECTION; STATISTICAL PROCESS-CONTROL; MINIMUM-VARIANCE CONTROL; CONTROL MPC PERFORMANCE; PARTIAL LEAST-SQUARES; CONTROL LOOPS SUBJECT; TO-RUN CONTROL; AUTOMATIC DETECTION;

D O I：

10.1002/cjce.20653

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

In many industrial plants, multiple, interconnected control loops are common. Their maintenance and improvement requires detailed controller performance assessment to determine not only whether they are behaving well, but also to determine the potential cause of any observed problems. Techniques for performance assessment can be divided into two broad categories (1) performance assessment of regulatory control loops; and (2) performance assessment of supervisory control loops that evaluate the economic performance of advanced control strategies, such as model predictive control (MPC). A comprehensive review of the literature on the industrial applications of performance assessment, as well as some of the currently available software, is also presented. (c) 2011 Canadian Society for Chemical Engineering

引用

页码：217 / 245

页数：29

共 197 条

[1] Assessing model prediction control (MPC) performance. 1. Probabilistic approach for constraint analysis [J].