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Performance analysis of three advanced controllers for polymerization batch reactor: an experimental investigation
journal contribution
posted on 2014-05-01, 00:00 authored by Anwar HosenAnwar Hosen, M A Hussain, F S Mjalli, Abbas KhosraviAbbas Khosravi, Douglas CreightonDouglas Creighton, Saeid NahavandiThe performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC. © 2013 The Institution of Chemical Engineers.
History
Journal
Chemical engineering research and designVolume
92Issue
5Pagination
903 - 916Publisher
ElsevierLocation
London, EnglandPublisher DOI
ISSN
0263-8762eISSN
1744-3563Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2014, ElsevierUsage metrics
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