Abstract
Cement decomposing furnace is a typical multi-variable, nonlinear, large delay and strong coupling complex control object, its difficult to establish accurate mathematical model, the conventional control algorithm is difficult to get satisfactory control effect. By applying adaptive BP(back propagation) algorithm in neural network modeling, make the neural network predicts the decomposing furnace outlet temperature, then modify the pulverized coal flow rate value that obtained by the fuzzy controller to control the decomposing furnace outlet temperature. The field application shows that the control software which is designed by the control algorithm in this paper responses quickly, the error between actual temperature and the expected value is small, it has a good reliability, adaptability and robustness.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
