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Lookup NU author(s): Dr Sulaiman Lawal,
Dr Jie Zhang
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© 2016 Elsevier B.V. Real-time sensor fault detection and fault tolerant control of a crude distillation unit is presented in this work. Dynamic principal component analysis is used to detect and identify faults on-line. When a sensor fault associated with a controlled variable is identified, an on-line soft-sensor built using dynamic principal component regression is used for feedback control. This is achieved through fault tolerant inferential controller which accommodate the sensor fault and maintain the integrity of the associated control loop in an online real-time manner. The specified products quality variables for the crude distillation unit, such as ASTM cut-points, flash point and viscosity at 210 F are maintained. Application results on the simulated crude distillation unit demonstrate the effectiveness of the proposed approach.
Author(s): Lawal SA, Zhang J
Publication type: Book Chapter
Publication status: Published
Book Title: Computer Aided Chemical Engineering
Online publication date: 25/06/2016
Acceptance date: 02/04/2016
Publisher: Elsevier B.V.
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