Toggle Main Menu Toggle Search

Open Access padlockePrints

Inferential Active Disturbance Rejection Control of a Distillation Column using Dynamic Principal Component Regression Models

Lookup NU author(s): Fahad Al Kalbani, Dr Jie ZhangORCiD


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


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.

Publication metadata

Author(s): Al Kalbani F, Zhang J

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 2015 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO)

Year of Conference: 2015

Pages: 358-364

Print publication date: 01/01/2015

Online publication date: 10/12/2015

Acceptance date: 01/01/1900



Library holdings: Search Newcastle University Library for this item

ISBN: 9789897581496