Differential recurrent neural network based predictive control

Al-Seyab, Rihab K. and Cao, Y (2006) Differential recurrent neural network based predictive control. Computer Aided Chemical Engineering, 21. pp. 1239-1244. ISSN 1570-7946

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Abstract

An efficient algorithm to train general differential recurrent neural networks is proposed. The trained network can be directly used as the internal model of a predictive controller. The efficiency and effectiveness of the approach are demonstrated through a two-CSTR case study, where a multi-layer perceptron differential recurrent network is adopted.

Item Type: Article
Article Type: Article
Uncontrolled Keywords: Predictive control; Recurrent neural networks; Nonlinear system identification; Nonlinear control
Subjects: T Technology > T Technology (General) > T55 Industrial Engineering. Management engineering
Divisions: Schools and Research Institutes > School of Business and Technology
Research Priority Areas: Applied Business & Technology
Depositing User: Rihab Al Seyab
Date Deposited: 01 Nov 2019 14:51
Last Modified: 01 Nov 2019 15:00
URI: http://eprints.glos.ac.uk/id/eprint/7476

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