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Performance analysis of two advanced controllers for polystyrene polymerization in batch reactor
conference contribution
posted on 2012-01-01, 00:00 authored by Anwar HosenAnwar Hosen, Abbas KhosraviAbbas Khosravi, Saeid Nahavandi, Douglas CreightonDouglas Creighton, M HussainThe performance of two advanced model based non-linear controllers is analyzed for the optimal setpoint tracking of free radical polymerization of styrene in batch reactors. Artificial neural network-based model predictive controller (NN-MPC) and generic model controller (GMC) are both applied for controlling the system. The recently developed hybrid model [1] as well as available literature models are utilized in the control study. The optimal minimum temperature profiles are determined based on Hamiltonian maximum principle. Different types of disturbances are artificially generated to examine the stability and robustness of the controllers. The experimental studies reveal that the performance of NN-MPC is superior over that of GMC.
History
Event
Engineering and Computer Science. World Congress (2012 : San Francisco, USA)Pagination
729 - 732Publisher
Newswood LimitedLocation
San Francisco, Calif.Place of publication
Hong KongStart date
2012-10-24End date
2012-10-26ISSN
2078-0958eISSN
2078-0966ISBN-13
9789881925244ISBN-10
988192524XLanguage
engPublication classification
E1 Full written paper - refereedTitle of proceedings
WCECS 2012 : Proceedings of the World Congress on Engineering and Computer ScienceUsage metrics
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