Pemodelan Generator Uap Berbasis Jaringan Saraf Tiruan dengan Algoritme Pelatihan BPGD-ALAM

https://doi.org/10.22146/ijeis.10766

Fadhlia Annisa(1*), Agfianto Eko Putra(2)

(1) 
(2) Jurusan Ilmu Komputer dan Elektronika, FMIPA UGM
(*) Corresponding Author

Abstract


Steam generator is unit plant which has nonlinear and complex system with multiple-input-multiple-output (MIMO) configuration which is hard to be modeled. Whereas, steam generator model is very useful to create simulation such as operator training simulator (OTS). The purpose of this research is to obtain model of steam generator which has 8 output parameters and 9 input parameters based neural network (NN) with BPGD-ALAM training algorithm. Data had been taken from steam generator of PT. Chevron Pacific Indonesia, Duri and it is divided into three types, i.e training data, validation data and testing data. Training data was used to obtain model for each ouput through training process. Verification model is also done for each epoch using validation data to monitor training process whether overfitting occurs or not. Eight NN model of each output which is obtained from training and verification, is tested using testing data for getting its performance. From the reseach results, architecture of neural network models are obtained with various configuration for each output with RMSE value under 9.71 %. It shows that model which has been obtained, close with steam generator real system.

Keywords


Steam Generator; Neural Network; Backpropagation; adaptive learning rate; adaptive momentum.

Full Text:

PDF


References

Man, G. N., 2001, A Model Predictive Controller for The Water Level Steam Generators, Journal of The Korean Nuclear Society, Nomor 1, volume 33,102-110.

Dorf, R. C. dan Bishop, R. H., 2011, Modern Control System, Edisi ke-12, Prentice Hall Inc., New Jersey.

Ramamoorthy, P. A., 2002, Nonlinear and Adaptive (Intelligent) System: Analysis, Modeling and Design – A Building Block Approach, University of Cincinnati, Cincinnati.

Willis, M. J. dan Ming, T. T, 2000, Advanced Process Control, http://www.dsea.unipi.it/Members/balestrinow/CP/file/introd_APC_SPC.pdf, diakses pada 4 September 2014.

Dai, H. dan Thompson, J. W., 1994, use of Neural Networks for Modelling The Steam Generator of A Nuclear Power Plant, Conference Proceedings of Electrical and Computer Engineering, Halifax.

Fausett, L., 1994, Fundamentals of Neural Networks: Architectures, Algorithms, and Applications, Prentice-Hall Inc., New Jersey.

Rehman, M. Z. dan Nawim N.M, 2012, Studying The Effect of Adaptive Momentum in Improving the Accuracy of Gradient Descent Back Propagation Algorithm on Classification Problems, International Conference Mathematical and Computational Biology 2011, Volume 9, 432-439

Hamid, N. A., Nawi, N. M., Ghazali, R. dan Salleh., 2011, Improvements of Back Propagation Algorithm Performance by Adaptively Changing Gain, Momentum and Learning Rate, International Journal on New Computer Architecture and Their Application, Volume 1, Nomor 4, 866-878.

Cimbala, J. M., 2011, Basic Statistics, https://www.mne.psu.edu/me345/Lectures/Basic_Statistics.pdf, diakses tanggal 9 September 2014.

Tim CleaverBrooks, 2011, Boiler Efficiency Guide, http://www.cleaverbrooks.com/ Reference-Center/Insights/Boiler-Efficiency-Guide.aspx, diakses tanggal 30 Januari 2015.

Wright, S. and Marwala, T., 2008, Artificial Intelligence Techniques for Steam Generator Modelling, Computing Research Repository, volume abs/0811.1711, http://arxiv.org/ftp/arxiv/papers/0811/0811.1711.pdf, diakses tanggal 22 Januari 2015.



DOI: https://doi.org/10.22146/ijeis.10766

Article Metrics

Abstract views : 2346 | views : 1982

Refbacks

  • There are currently no refbacks.




Copyright (c) 2017 IJEIS - Indonesian Journal of Electronics and Instrumentation Systems

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



Copyright of :
IJEIS (Indonesian Journal of Electronics and Instrumentations Systems)
ISSN 2088-3714 (print); ISSN 2460-7681 (online)
is a scientific journal the results of Electronics
and Instrumentations Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijeis.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijeis



View My Stats1
View My Stats2