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By combining the Back-Propagation(BP)neural network with conventional proportional Integral Derivative(PID)controller,a new temperature control strategy of the export steam in supercritical electric power plant is put forward.This scheme can effectively overcome the large time delay,inertia of the export steam and the influence of object in varying operational parameters.Thus excellent control quality is obtained.The present paper describes the development and application of neural network based controller to control the temperature of the boiler’s export steam.Through simulation in various situations,it validates that the control quality of this control system is apparently superior to the conventional PID control system.
By combining the Back-Propagation (BP) neural network with conventional proportional Integral Derivative (PID) controller, a new temperature control strategy of the export steam in supercritical electric power plant is put forward. This scheme can effectively overcome the large time delay, inertia of the export steam and the influence of object in varying operational parameters .hus excellent control quality is obtained. The present paper describes the development and application of neural network based controller to control the temperature of the boiler’s export steam.Through simulation in various situations, it validates that the control quality of this control system is apparently superior to the conventional PID control system.