Neural Network Modeling For Main Steam Temperature System
DOI:
https://doi.org/10.11113/jt.v69.3151Keywords:
Main steam temperature, neural network, coal fired power plantAbstract
Main Steam Temperature (MST) is non-linear, large inertia, long dead time and load dependant parameters. The paper present MST modeling method using actual plant data by utilizing MATLAB's Neural Network toolbox. The result of the simulation showed the MST model based on actual plant data is possible but the raw data need to be pre-processed for better output. Generator output, total main steam flow, main steam pressure and total spray flow are four main parameters affected the behavior of MST in coal fired power plant boiler.
References
Ilhan Kocaarslan, Ertugrul Cam, Hasan Tiryaki. 2005. A Fuzzy Logic Controller Application For Thermal Power Plants. Energy Conversion and Management. 47: 442–458.
S. Matsumura, K. Ogata, S. Fujii, H.Shoya and H. Nakamura. 1994. Adaptive Control for the Steam Temperature of Thermal Power Plants. Control Engineering Practice. 2(4): 567–575.
Hui Peng, Toru Ozaki, Yukihiro Toyoda, Keiji Oda. 2001. Exponential ARX Model-Based Long-Range Predictive Control Strategy for Power Plants. Control Engineering Practice. 9: 1353–1360.
Tommy Moelbak. 1998. Advanced Control of Superheater Steam Temperature– An Evaluation Based On Practical Applications. Control Engineering Practice. 7: 1–10.
N. A Mazalan, A. A Malek, Mazlan A. Wahid, M. Mailah, Aminuddin Saat, Mohsin M. Sies. 2013. Main Steam Temperature Modeling Based on Levenberg-Marquardt Learning Algorithm. Applied Mechanics and Materials. 388: 307–311.
Satish Kumar. 2004. Neural Network: A Classroom Approach. Tata McGraw-Hill Education Private Limited, New Delhi.
McCulloch, W.S., and Pitts, W. 1943. A Logical Calculus of the Ideas Immanent in Nervous Activity. Bull. of Mathematical Biophysics. 5: 115–133.
von Neumann, J. 1951. The General and Logical Theory of Automata. Cerebral Mechanisms of Behavior: The Hixon Symposium, Wiley, New York, NY. 1–32.
Hebb, D. O. 1949. The Organization Of Behavior. John Wiley, New York, NY.
Turing, A. 1950. Computing Machinery and Intelligence. Mind. 59: 433–460.
Rosenblatt, F. 1958. The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain. Psychological Review. 65: 386–408.
Rosenblatt, F. 1960. On the Convergence of Reinforcement Procedures in Simple Perceptrons. Tech. Rep. VG-1196-G-4. Cornell Aeronautical Laboratory, Buffalo, NY.
Rosenblatt, F. 1960. Perceptron Simulation Experiments. Proceedings of the Institute of Radio Engineers. 48: 301–309.
Rosenblatt, F. 1962. Principles of Neurodynamics. Spartan Books, Washington.
Minsky, M., and S. Papert. 1969. Perceptrons: An Introduction to Computational Geometry. MIT Press, Cambridge, MA.
Werbos, P. J. 1974. Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences. PhD Thesis, Harvard University, Cambridge, MA.
McClelland, J. L., and Rummelhart, D. 1986. Parallel Distributed Processing. Vol. I and II. MIT Press, Cambridge, MA.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
