Authors:
Fahad Al Kalbani
and
Jie Zhang
Affiliation:
Newcastle University, United Kingdom
Keyword(s):
Distillation Column, Composition Control, Inferential Control, Active Disturbance Rejection Control, Principal Component Regression, Estimator.
Related
Ontology
Subjects/Areas/Topics:
Engineering Applications
;
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Quality Control and Management
;
Real-Time Systems Control
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
System Modeling
Abstract:
This paper presents a multivariable inferential active disturbance rejection control (ADRC) method for product composition control in distillation columns. The proposed control strategy integrates ADRC with inferential feedback control. In order to overcome long time delay of gas chromatography in measuring product compositions, static and dynamic estimators for product compositions have been developed. The top and bottom product compositions are estimated using multiple tray temperatures. In order to overcome the colinearity issue in tray temperatures, principal component regression is used to build the estimator. The proposed technique is applied to a simulated methanol-water separation column. It is shown that the proposed control strategy gives good setpoint tracking and disturbance rejection control performance.