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PID controller tuning for a multivariable glass furnace process by genetic algorithm

Rajarathinam, K, Gomm, JB, Yu, DL and Abdelhadi, AS (2016) PID controller tuning for a multivariable glass furnace process by genetic algorithm. International Journal of Automation and Computing, 13 (1). pp. 64-72. ISSN 1476-8186

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Standard genetic algorithms (SGAs) are investigated to optimise discrete-time proportional-integral-derivative (PID) controller parameters, by three tuning approaches, for a multivariable glass furnace process with loop interaction. Initially, standard genetic algorithms (SGAs) are used to identify control oriented models of the plant which are subsequently used for controller optimisation. An individual tuning approach without loop interaction is considered first to categorise the genetic operators, cost functions and improve searching boundaries to attain the desired performance criteria. The second tuning approach considers controller parameters optimisation with loop interaction and individual cost functions. While, the third tuning approach utilises a modified cost function which includes the total effect of both controlled variables, glass temperature and excess oxygen. This modified cost function is shown to exhibit improved control robustness and disturbance rejection under loop interaction. © 2015 Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg

Item Type: Article
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s11633-015-0910-1
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Electronics & Electrical Engineering (merged with Engineering 10 Aug 20)
Publisher: Springer
Date Deposited: 02 Sep 2016 10:44
Last Modified: 04 Sep 2021 12:34
DOI or ID number: 10.1007/s11633-015-0910-1
URI: https://researchonline.ljmu.ac.uk/id/eprint/4075
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