Nonlinear model predictive control for the ALSTOM gasifier

Al-Seyab, Rihab ORCID: 0000-0001-6384-193X and Cao, Y (2006) Nonlinear model predictive control for the ALSTOM gasifier. Nonlinear model predictive control for the ALSTOM gasifier, 16. pp. 795-808. doi:10.1016/j.jprocont.2006.03.003

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Text (Peer Reviewed Version) Al Sayeb, R.K. (2006) Nonlinear model predictive control for the ALSTOM gasifier.pdf - Draft Version Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (778kB) | Preview

Abstract

In this work a nonlinear model predictive control based on Wiener model has been developed and used to control the ALSTOM gasifier. The 0% load condition was identified as the most difficult case to control among three operating conditions. A linear model of the plant at 0% load is adopted as a base model for prediction. A nonlinear static gain represented by a feedforward neural network was identified for a particular output channel—namely, fuel gas pressure, to compensate its strong nonlinear behaviour observed in open-loop simulations. By linearising the neural network at each sampling time, the static nonlinear model provides certain adaptation to the linear base model at all other load conditions. The resulting controller showed noticeable performance improvement when compared with pure linear model based predictive control.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Predictive control; Gasification Wiener model; Feed forward neural networks; Linearisation
Subjects:	T Technology > T Technology (General) T Technology > T Technology (General) > T55 Industrial Engineering. Management engineering
Divisions:	Schools and Research Institutes > School of Education and Science
Research Priority Areas:	Applied Business & Technology
Depositing User:	Rihab Al Seyab
Date Deposited:	01 Nov 2019 13:17
Last Modified:	01 Sep 2023 11:44
URI:	https://eprints.glos.ac.uk/id/eprint/7478

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