Design of fuzzy neural network based control system for cement rotary kiln

This paper presents a fuzzy neural network control system for the process of cement production with rotary cement kiln. Since the dynamic characteristics and reaction process parameters are with large inertia, pure hysteresis, nonlinearity and strong coupling, a fuzzy neural network controller combining both the advantages of neural network and fuzzy control is applied. This fuzzy neural network controller adjusts the parameters of membership functions in order to acquire the required control performance. The fuzzy neural network is an adaptive neural network whose parameters can be corrected by learning algorithms automatically. The main control system structure includes three control loops as the pressure control loop, the burning zone control loop and the back-end of kiln temperature control loop. The simulation results show the effectiveness of the control scheme with quick response time and lower overshoot, also with small temperature deviation.