Premium
A robust tuning procedure for adaptive inferential control
Author(s) -
Brodie K. A.,
Tham M. T.,
Willis M. J.
Publication year - 1999
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/(sici)1099-1115(199903)13:2<85::aid-acs524>3.0.co;2-u
Subject(s) - robustness (evolution) , adaptive control , computer science , robust control , control engineering , key (lock) , control theory (sociology) , adaptive sampling , control (management) , process (computing) , inference , control system , engineering , artificial intelligence , mathematics , biochemistry , chemistry , statistics , computer security , monte carlo method , electrical engineering , gene , operating system
Inferential estimation and control are techniques tailored for processes with severe sampling limitations on key process measurements. Often such systems have complex, time‐varying dynamics making sustainable control performance an elusive target. As potential solutions, adaptive and robust control have been suggested with varying degrees of success. In this work, robust control principles are used to develop a tuning procedure for an adaptive inferential control algorithm, in order to monitor and optimize control performance. The primary advantage of the technique is that performance‐robustness targets are maintained despite changes in system dynamics. A case study is used to demonstrate the utility of the technique highlighting the performance enhancements provided by the combination of adaptive and robust inferential control. Copyright © 1999 John Wiley & Sons, Ltd.