Neural network based modelling and control in batch reactor

Mujtaba, I.M. and Aziz, N. and Hussain, Mohd Azlan (2006) Neural network based modelling and control in batch reactor. Chemical Engineering Research and Design, 84 (A8). pp. 635-644. ISSN 0263-8762, DOI https://doi.org/10.1205/Cherd.05096.

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Official URL: https://doi.org/10.1205/cherd.05096

Abstract

The use of neural networks (NNs) in all aspects of process engineering activities, such as modelling, design, optimization and control has considerably increased in recent years (Mujtaba and Hussain, 2001). In this work, three different types of nonlinear control strategies are developed and implemented in batch reactors using NN techniques. These are generic model control (GMC), direct inverse model control (DIC) and internal model control (IMC) strategies. Within the control strategies, NNs have been used as dynamic estimator, dynamic model (forward model) and control (inverse model). An exothermic complex reaction scheme in a batch reactor is considered to explain all these control strategies and their robustness. A dynamic optimization problem with a simple model is solved a priori to obtain optimal operation policy in terms of the reactor temperature with an objective to maximize the desired product in a given batch time. The resulting optimal temperature policy is used as set-point in the control study. All types of controllers performed well in tracking the optimal temperature profile and achieving target conversion to the desired product. However, the NNs used in DIC and IMC controllers need training beyond the nominal operating condition to cope with uncertainties better.

Item Type: Article
Funders: UNSPECIFIED
Additional Information: 075NC Times Cited:17 Cited References Count:20
Uncontrolled Keywords: batch reactor; dynamic optimization; control; neural networks; inverse modelling; dynamic optimization; temperature control; strategy.
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 04:33
Last Modified: 25 Sep 2019 09:16
URI: http://eprints.um.edu.my/id/eprint/7053

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