Review of the applications of neural networks in chemical process control—simulation and online implementation

Azlan Hussain, Mohamed (1999) Review of the applications of neural networks in chemical process control—simulation and online implementation. Artificial Intelligence in Engineering, 13 (1). pp. 55-68. ISSN 0954-1810

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Abstract

As a result of good modeling capabilities, neural networks have been used extensively for a number of chemical engineering applications such as sensor data analysis, fault detection and nonlinear process identi®cation. However, only in recent years, with the upsurge in the research on nonlinear control, has its use in process control been widespread. This paper intend to provide an extensive review of the various applications utilizing neural networks for chemical process control, both in simulation and online implementation. We have categorized the review under three major control schemes; predictive control, inverse-model-based control, and adaptive control methods, respectively. In each of these categories, we summarize the major applications as well as the objectives and results of the work. The review reveals the tremendous prospect of using neural networks in process control. It also shows the multilayered neural network as the most popular network for such process control applications and also shows the lack of actual successful online applications at the present time. q1998 Elsevier Science Ltd. All rights reserved.

Item Type: Article
Uncontrolled Keywords: Chemical process control; Neural networks; Simulation; Online application.
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: 11 Jul 2013 01:03
Last Modified: 11 Jul 2013 01:03
URI: http://eprints.um.edu.my/id/eprint/7097

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