PID control of evaporation temperature control system based on fuzzy RBF neural network

Abstract In this thesis, a fuzzy RBF neural network PID (RBFfnn-pid) control method is designed for temperature deviation concerning the steam curing system in kettle of aerated concrete block production line. The (TCS) models are established respectively under and RBFfnn-pid. Then, effect analyzed by simulation different situations. results show that, condition step signal inputting, RBFfnn-pid shortens rising time 160 s reduces overshoot 8% compared with controlling means. When stable state, then interference added, which contrast to means PID, adjusting set value shortened 70 seconds there no overshoot. enables parameters steaming be adjusted optimum quickly iteratively, improves accuracy.