Implementasi Kontrol Model Prediksi Berbasis ANFIS Pada Mesin Penghasil Uap Air

https://doi.org/10.22146/ijeis.7158

Rangga Kurniawan Ladioktaviagusdi(1*), Raden Sumiharto(2),

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

Abstract


Steam generator has problem such as dependent variable on the output parameters, therefore it is needed a way to get system behavior of steam generator which is represented by model of the plant. Implementation of the model predictive control in this research was represented by using simulation, so the object that was controlled was virtual steam generator. In this research was used MATLAB software as a virtual steam generator and also for computes ANFIS, whereas the LabVIEW software was used as a representation of control room.

From the research, it was found the best parameters for each ANFIS that was used as a model unit in the model predictive control, that was by using historical data 4th as much as 800 datas, the percentage ratio of learning for training data and checking data on each ANFIS for each model structures sequentially by 90% and 10%, except the percentage ratio for ANFIS on water flow parameter sequentially by 80% and 20%. The results of validation RMSE (Root Mean Square Error) by testing for 100 datas, it was obtained values as follows: water flow=1.9941, water pressure=48.0236, air flow=604.0621, fuel gas pressure=0.7087, fuel gas temperature=18.6594, O2 content=0.9591, steam pressure=76.1557, steam quality=3.9734 and steam flow=264.9173.


Keywords


Steam generator, model predictive control, modeling, ANFIS, MATLAB, LabVIEW

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References

Buragohain, M. dan Mahanta, C., 2006. ANFIS Modelling of Nonlinear System Based on Vfold Technique. Departement of ECE, Indian Institute of Technology Guwahati, Guwahati, Assam.
[2]Halvorsen, H., 2011. Model Predictive in LabVIEW.Departement of Electrical Engineering, Information Technology and Cybernetics, Telemark University College.
[3]Sivakumar, R. dan Balu, K., 2010. ANFIS Based Destillation Column Control. Departement of Electronics and Instrumentation, St. Joseph’s College, India.
[4]Kuniawan, R., 2012. Laporan Kerja Praktek, Analisa Kinerja Steam Generator Menggunakan Artificial Intelligence. PT. Chevron Pacific Indonesia, Duri.



DOI: https://doi.org/10.22146/ijeis.7158

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Indonesian Journal of Electronics and Instrumentations Systems
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