International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 4, No. 4, 8 Apr. 2012
Cover page and Table of Contents: PDF (size: 2504KB)
Parameter Tuning via Genetic Algorithm of Fuzzy Controller for Fire Tube Boiler
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Author(s)
Osama I. Hassanein
1,*
Ayman A. Aly
2,3
Ahmed A. Abo-Ismail
4
Index Terms
Fire Tube Boiler, Fuzzy Logic Control, Genetic Algorithm
Abstract
The optimal use of fuel energy and water in a fire tube boiler is important in achieving economical system operation, precise control system design required to achieve high speed of response with no overshot. Two artificial intelligence techniques, fuzzy control (FLC) and genetic-fuzzy control (GFLC) applied to control both of the water/steam temperature and water level control loops of boiler. The parameters of the FLC are optimized to locating the optimal solutions to meet the required performance objectives using a genetic algorithm. The parameters subject to optimization are the width of the membership functions and scaling factors. The performance of the fire tube boiler that fitted with GFLC has reliable dynamic performance as compared with the system fitted with FLC.
Cite This Paper
Osama I. Hassanein, Ayman A. Aly, Ahmed A. Abo-Ismail, "Parameter Tuning via Genetic Algorithm of Fuzzy Controller for Fire Tube Boiler", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.4, pp.9-18, 2012. DOI:10.5815/ijisa.2012.04.02
Reference
[1]Anderson J. H. “Dynamic Control of a Power Boiler” Proc. IEE Vol. 116, No. 7, pp. 1257-1268, (1969).
[2]Chen, Y. C., et al., “A study on calculation method of boiler efficiency,” Technical Report No. EMR-024, Energy and Mining Service Organization, ITRI Taiwan (1983).
[3]Chi, J. and Kelly, G. E., “A method for estimating the seasonal performance of residential gas and oil fired heating systems”, ASHRAE Trans. Vol. 84, pt. 1, pp.405-420, (1978).
[4]Chi, j., Lih, C. and Didion D. A. “ A commercial heating boiler transient analysis simulation model (DEPAB2)” NBSIR 83-2683, NIST, (1983).
[5]Huang, B. J., Yen, R. H., and Shyu, W. S. “A steady state thermal performance model of Fire tube shell boilers” ASME, J. of Gas Turbine and Power, Vol. 110, pp. 173-179, (April 1988).
[6]Cheol P. and Liu, S. T. “Performance of a commercial hot water boiler,” November, NISTIR 6226, U. S. Department of commerce, (1998).
[7]Chien K. L., Ergin, E. I., Ling C. and Lee, A., “Dynamic Analysis of a Boiler” Trans. of ASME, Vol. 80, pp. 1809-1819, (1958).
[8]De Mellow F. P. “Boiler Models for System Dynamic Performance Studies” IEEE Trans. on Power Systems, Vol. 6, No. 1, (February 1991).
[9]Dechamps , P. J. “Modeling the transient behavior of heat recovery steam generators” Proc. Of the Inst. Of Mech. Eng., Pt. A, Vol. 209, No. A4, (1995).
[10]Nicholson, H., “Dynamic Optimization of a Boiler” Proc. IEEE, Vol. 111, No.8, pp.1479-1499, (1964).
[11]Nicholson, H., “Integrated Control of a Nonlinear Boiler Model” Proc. IEE, Vol. 114, No. 10, pp. 1569-1576, (1967).
[12]Ali Yousef and Ayman A. Aly, “Effect of Non-linearities in Fuzzy Approach for Control A Two –Area Interconnected Power System”, 2010 IEEE International Conference on Mechatronics and Automation (ICMA 2010) China, August 4-7, 2010.
[13]Ayman A. Aly, “Optimization of Desiccant Absorption System Using a Genetic Algorithm”, Journal of Software Engineering and Applications, Vol. 4, No.9, pp 527-533, Sep. 2011, USA.
[14]Mitchell, M., “An Introduction to genetic algorithms”, MIT Press, (1996).
[15]O. I. Hassanin and Ayman A. Aly “Genetic PID Controller for a Fire Tube Boiler,” International Conference on Computational Cybernetics 2004 in Vienna, Austria.
[16]Salman, S. A., Turk, A., abd-elhafez, and Abo-Ismail A., “Fuzzy control of fire tube boilers” IEEE 7th International Conference on Intelligent Engineering Systems, pp. 323-328, (March 2003).