Performance analysis of three advanced controllers for polymerization batch reactor: An experimental investigation |
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| Authors: | Mohammad Anwar Hosen Mohd Azlan Hussain Farouq Sabri Mjalli Abbas Khosravi Douglas Creighton Saeid Nahavandi |
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| Affiliation: | 1. Centre for Intelligent Systems Research (CISR), Deakin University, Locked Bag 20000, Waurn Ponds, Geelong, VIC 3220, Australia;2. Chemical Engineering Department, University of Malaya, Kuala Lumpur, Malaysia;3. Petroleum and Chemical Engineering Department, Sultan Qaboos University, Muscat, Oman |
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| Abstract: | The 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. |
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| Keywords: | Model based controller NN-MPC FLC GMC Hybrid model Polystyrene |
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