Temperature control in big-scale rotary kiln by using grey neural network

In large-scale rotary kiln applications, it is important to control the internal temperature of the kilns. However, there are many problems in designing such a control system due to long system´s response delay, dead-zone and saturation of the actuator mechanisms, uncertainties in the system model and parameters, and process noise. To overcome these problems, this article has proposed a new type of kiln temperature controller, which is based on the grey theory and neural network (NN). It can effectively solve the problems mentioned above by incorporating predictive ability of grey system and adaptive ability of a NN. We tested the proposed controller via extensive simulation and the result was very promising.