Air-Fuel-Ratio optimal control of a gas heating furnace based on fuzzy neural networks

Authors:
Heng Cao;Ding Du;Yunhua Peng;Yuhai Yin
Affiliations:
School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China;School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China;Shanghai Baosteel Chemical Co. Ltd., Shanghai, China;School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Year:
2006

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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.