Abstract
Based on Neural Network BP algorithm and self-optimizing control, taking gas heating furnace air-fuel-ratio optimized control as goal, a new heating furnace intelligent control algorithm is raised and applied in the practice. Comparing fuzzy neural network hybrid algorithm and PID control algorithm, with gas heating furnace energy-saving control reconstruct, new algorithm can achieve function of automatic tracking calorific value variable and adjusting air-fuel-ratio. The characteristics of this algorithm are high precision and reliability, and suitable for project application.
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© 2006 Springer-Verlag Berlin Heidelberg
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Cao, H., Du, D., Peng, Y., Yin, Y. (2006). Air-Fuel-Ratio Optimal Control of a Gas Heating Furnace Based on Fuzzy Neural Networks. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_128
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DOI: https://doi.org/10.1007/11760191_128
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
Online ISBN: 978-3-540-34483-4
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