Recent developments in multivariable controller performance monitoring

被引:89
作者
Qin, S. Joe [1 ]
Yu, Jie [1 ]
机构
[1] Univ Texas, Dept Chem Engn, Austin, TX 78712 USA
关键词
MIMO control performance monitoring; minimum variance; model predictive control; covariance based monitoring; worst performance directions; EXPLICIT SOLUTION; DIAGNOSIS; ISSUES;
D O I
10.1016/j.jprocont.2006.11.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we give a critical overview of recent development in MIMO control performance monitoring. We discuss a number of MIMO control benchmarks including minimum variance, LQG, and user selected benchmarks. Performance measures are extended from variance based measures in SISO control to covariance based measures in MIMO control. Pros and cons of various benchmarks are discussed. The diagnosis of poor control performance relative to a benchmark is a major focus of the paper. We argue that in the MIMO setting, the worst performance directions should be analyzed from data to yield meaningful diagnosis information. Therefore, multivariate statistics should be applied for the diagnosis of the worst performance directions, rather than one loop at a time, much like its use in multivariate process monitoring. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:221 / 227
页数:7
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