Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)

The Application of Thermodynamic Parameter Model Based on RGSA-RBFNN in Vacuum Resurgence Control Process

Authors
Xinye Li, Yekuan Luo, Jiajing Wang, Yushan Hao
Corresponding Author
Xinye Li
Available Online August 2018.
DOI
10.2991/caai-18.2018.1How to use a DOI?
Keywords
vacuum resurgence; thermodynamic parameter model; RGSA; GSA; RBFNN
Abstract

In traditional vacuum resurgence control process, there are some problems such as insufficient moisture regain, unsatisfactory moisture content absorption and large steam loss. In order to solve these problems, we put forward the vacuum pre-conditioner’s thermodynamic parameter model to control the vacuum resurgence process quantitatively. At first we proposed an Reinforcement Gravitational Search Algorithm (RGSA) to optimize the RBF neural network parameters, and then used the RGSA-RBFNN, GSA-RBFNN, RBFNN to establish the corresponding thermodynamic parameter model of the vacuum pre-conditioner. At last we used test data set to verify the model established by those three kinds of neural network. The results showed that RGSA-RBFNN has very strong function mapping ability, higher precision and more advantages than GSA-RBFNN or RBFNN. Using the model to control the process of vacuum resurgence, the moisture content of tobacco strips increases from 8% to 15%, which is 4 percentage points higher than 11% of the unmodeled one. The moisture content of tobacco leaf has been improved greatly. It has certain guiding significance for tobacco strips production of vacuum pre-conditioner.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
August 2018
ISBN
978-94-6252-595-5
ISSN
2589-4919
DOI
10.2991/caai-18.2018.1How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xinye Li
AU  - Yekuan Luo
AU  - Jiajing Wang
AU  - Yushan Hao
PY  - 2018/08
DA  - 2018/08
TI  - The Application of Thermodynamic Parameter Model Based on RGSA-RBFNN in Vacuum Resurgence Control Process
BT  - Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
PB  - Atlantis Press
SP  - 1
EP  - 5
SN  - 2589-4919
UR  - https://doi.org/10.2991/caai-18.2018.1
DO  - 10.2991/caai-18.2018.1
ID  - Li2018/08
ER  -