Study On The Intelligent Control Of Combustion System Of Circulating Fluidized Bed Boiler

Bed temperature and mainstream pressure are important parameter of circulating fluidized bed boiler (CFBB) combustion control system. To maintain them normal is key to the stable and economic operation of CFBB. By the idea of dynamic mechanism and macroscopical control modeling, mathematical model describing the dynamic characteristic of bed temperature and mainstream pressure of 410t/h CFBB is proposed in this thesis. Two fuzzy neural network control systems are designed: fuzzy neural network self-learning control system and fuzzy neural cell complex control system. Based on the modeling, computer simulation is carried out. The simulation results are satisfactory in case of control effects. The results indicate that the control quality, the speediness, the robustness and the ability of anti-disturbance of fuzzy neural network control system are all superior to the general PID control system.