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Circulating fluidized bed boiler combustion system is a complex, large time delay, strong coupling and non-linearity system. Keeping the regular bed temperature is the key point of making the circulating fluidized bed boiler work stably. Aimed at the weak anti-interference ability, long stable time and low control precision in the traditional CFB boiler bed temperature controller, an new CFB boiler bed temperature controller for improved Neural Dynamic Programming(NDP) methods which the model network is Elman neural network was designed. Finally, the simulation was finished on the circulating fluidized bed boiler combustion system. Comparing with the traditional PID controller, the results show that this new controller not only can better fitting practical mathematical model of CFB boiler combustion system, but also has many advantages such as good dynamics, fast convergence rate, high controlled resolution.