The Control Optimization Research Of Ash Recycling System Of Circulating Fluidized Bed Boiler

Ash recycling system is a unique system of circulating fluidized bed(CFB) boiler. This paper has detailed analyzed the process of ash recycling system. The amount of return materials has an important role in bed temperature stability. Changing return materials can control the bed temperature, when the bed temperature rises, we can increase the amount of return materials to maintain it constant, the contrary is also true. In actual operation, we can't get the return materials, but it increases with the return fluidizing air increasing by previous studies. In this paper, we can changing the return fluidizing air to adjust the return materials, then to balance the bed temperature fluctuations caused by the disturbance, reducing system latency and achieving the ash recycling system optimization.CFB boiler is a control object with many parameters, nonlinear, time-varying, large delay, multivariable coupling and difficult to obtain accurate mathematical model, using conventional control methods are difficult to achieve the desired control effect. But the fuzzy neural network control synthesis the advantages of fuzzy control and neural network, not only making the fuzzy control with learning function, but also making the neural network with fuzzy information processing functions, for judgment and decision making.In this paper, adding compensation algorithm to the fuzzy network, and using the data of Baima power plant to train the network, the result is better than the conventional fuzzy neural network. This paper established a return materials control system based on the compensatory fuzzy neural network, the inputs are the change and change rate of boiler bed temperature, and the output is return fluidizing air. Then establishing a simulink simulation model, and compared with the conventional PID, we have confirmed that the compensatory fuzzy neural network is important to optimization of the ash recycling system.