It is difficult for the conventional PID control to adjust with the change of dynamic characteristics of the plants. By combing the state feedback based on Elman neural network state observer and the conventional PID, a new control system was presented in this paper. The unmeasurable states of the system was reconstructed through NN observer, the adaptivabilty of system was improved by state feedback. A simulation for power plant super-heated steam temperature control system using presented method is carried out, and resulting in that the control system performance is better than the conventional cascade control system.

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