Differential recurrent neural network based predictive control

Al-Seyab, Rihab ORCID: 0000-0001-6384-193X and Cao, Y (2006) Differential recurrent neural network based predictive control. Computer Aided Chemical Engineering, 21. pp. 1239-1244. doi:10.1016/S1570-7946(06)80216-6

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Text (Peer Reviewed Version) Al Sayeb, R.K. (2006) Differential recurrent neural network based predicative control.pdf - Draft Version Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (1MB) | Preview

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 > Gloucestershire Business School
Research Priority Areas:	Applied Business & Technology
Depositing User:	Rihab Al Seyab
Date Deposited:	01 Nov 2019 14:51
Last Modified:	30 Apr 2021 12:15
URI:	http://eprints.glos.ac.uk/id/eprint/7476

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