A Study On The Superheated Steam Temperature Of Straw Furnace Control Based On Neural Network

Straw boiler superheated steam temperature control system is to improve the efficiency of the heat units and units to ensure the safe operation of an important part, superheated steam temperature of the factors that interfere with a lot of very large frequent disturbance, under variety of disturbances, superheated steam temperature with the dynamic characteristics of large delay, large inertia, and non-linear time-varying characteristics. In view of the complex hot working process's nonlinear response, this article proposed one kind based on the immunity principle radial direction primary function neural network misalignment model identification, carries on the complex hot working process using this kind of RBF neural network the misalignment model identification. The simulation research indicated, this kind of modelling computation load is not only small, the precision is high, moreover recognizes the misalignment model may fit many linear models, realizes the multi-model optimized control.