Al-Seyab, Rihab K. 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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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 |
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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 |
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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 |
Research Priority Areas: | Applied Business & Technology |
Depositing User: | Rihab Al Seyab |
Date Deposited: | 01 Nov 2019 14:51 |
Last Modified: | 01 Jun 2020 14:47 |
URI: | http://eprints.glos.ac.uk/id/eprint/7476 |
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