In order to control working fluid outlet temperature efficiently and maintain the stable operation of the heat exchanger

aiming at characteristics of Smith predicted control algorithm and radial basis function（ RBF）neural network of single neuron PID control algorithm

control strategy combined Smith control algorithm and RBF neural network single neuron PID is proposed. Smith predicted control algorithm is improved in the structure to reduce its dependence on the model. Meanwhile

the anti-interference ability of RBF neural network PID is increased. The simulation results show that the proposed algorithm can make the control performance and the antiinterference ability significantly better than others when it is applied to temperature control system of heat exchanger.