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Actuator Fault Monitoring and Fault Tolerant Control in Distillation Columns

Lookup NU author(s): Dr Sulaiman Lawal, Dr Jie Zhang

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


Abstract

This paper presents, from a practical viewpoint, an investigation of real-time actuator fault detection, propagation and accommodation in distillation columns. Addressing faults in industrial processes, coupled with the growing demand for higher performance, improved safety and reliability necessitates implementation of easily understood less complex alternative control strategies in the events of malfunctions in actuators, sensors and or other system components. This work demonstrates frugality in the design and implementation of fault tolerant control system by integrating fault detection and diagnosis techniques with simple active restructurable feedback controllers with backup feedback signals and switchable reference points to accommodate actuator fault in distillation columns based on a priori assessed control structures. A multivariate statistical process monitoring based fault detection and diagnosis technique through dynamic principal components analysis is integrated with one-point control or alternative control structure for prompt and effective fault detection, isolation and accommodation. The work also investigates effects of disturbances on fault propagation and detection. Specifically, the reflux and vapor boil-up control strategy used for a binary distillation column during normal operation is switched to one point control of the more valued product by utilizing the remaining healthy actuator. The proposed approach was implemented on two distillation processes - a simulated methanol-water separation column and the benchmark Shell standard heavy oil fractionation process to assess its effectiveness.


Publication metadata

Author(s): Lawal SA, Zhang J

Publication type: Article

Publication status: Published

Journal: International Journal of Automation and Computing

Year: 2017

Volume: 14

Issue: 1

Pages: 80-92

Print publication date: 01/02/2017

Online publication date: 03/01/2017

Acceptance date: 03/06/2016

Date deposited: 16/08/2016

ISSN (print): 1476-8186

ISSN (electronic): 1571-8520

Publisher: Springer

URL: http://dx.doi.org/10.1007/s11633-016-1037-8

DOI: 10.1007/s11633-016-1037-8


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