Research and application of neural network PID control in cement industry

As various parameters of cement rotary kiln temperature control system means the relationships of strong coupling, nonlinearity and fast time-variety, there are many factors impact the temperature of combustion. Aiming at the constant control, an improved PID control method based on RBF neural network is proposed, and a new model of temperature intelligent controller to control nonlinear systems for multi-variable control was presents in the paper. Mathematical model of RBFNN PID controller was built, and the control simulation of entire model is realized by Matlab. The result of simulation indicates that the improved control algorithm offers better control effects than traditional PID control.