Multi-Parameter Control for Precalciner Kiln System of Cement Using Adaptive Dynamic Programming

There are many factors that can affect the calciner process of cement production, such as highly nonlinearity and time-lagging, making it very difficult to establish an accurate model of the cement kiln system. In order to reduce transport energy consumption and to ensure the quality of cement clinker burning, one needs to explore different control methods from the traditional way. In this paper ADHDP of adaptive dynamic programming family is used in cement kiln system to control the temperature of furnace export and oxygen content of exhaust. Also the BP network of artificial neural network is used to accomplish the network modeling, and action and critic modules of the algorithm. The results of simulation show that, after the fluctuations in the early control period, the controlled parameters tend to be stabilized guaranteeing the quality of cement clinker calcining.