Control of a batch polymerization system using hybrid neural network first principle model

Wei, N.C. and Hussain, M.A. and Wahab, A.K.A. (2007) Control of a batch polymerization system using hybrid neural network first principle model. Canadian Journal of Chemical Engineering, 85 (6). pp. 936-945. ISSN 0008-4034

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Abstract

In this work, the utilization of neural network in hybrid with first principle models for modelling and control of a batch polymerization process was investigated. Following the steps of the methodology, hybrid neural network (HNN) forward models and HNN inverse model of the process were first developed and then the performance of the model in direct inverse control strategy and internal model control (IMC) strategy was investigated. For comparison purposes, the performance of conventional neural network and PID controller in control was compared with the proposed HNN. The results show that HNN is able to control perfectly for both set points tracking and disturbance rejection studies.

Item Type: Article
Additional Information: 253IU Times Cited:0 Cited References Count:24
Uncontrolled Keywords: Batch polymerization, First principle model, Hybrid neural networks, Model-based control, Modelling, Control equipment, Mathematical models, Neural networks, Three term control systems, Internal model control (IMC), Polymerization.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 10 Jul 2013 03:55
Last Modified: 27 Oct 2014 06:17
URI: http://eprints.um.edu.my/id/eprint/7046

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