Hybrid intelligent control of raw meal silo weight with time delay in raw meal supply process

Abstract

A hybrid intelligent control strategy for raw meal supply process has been proposed and successfully applied to an annual clinker production capacity of 0.73 million ton of Jiuganghongda Cement Plant in China. The raw meal supply process is a time-varying, long time delay and large inertia system. In addition, a large fluctuation of the raw meal flow affects the stability of the raw meal silo weight. There is often a phenomenon that silo weight is close to zero or overweight, resulting in discontinuity of the raw meal decomposition process in calciner and the clinker calcination process in rotary kiln. Therefore, it is difficult to control efficiently the process by conventional control methods. In this paper, a hybrid intelligent control method that incorporates PI control and fuzzy control with rule-based reasoning feedforward control is presented. Condition identification module in switching rules identifies current conditions according to the input variables. Industrial application results show that the hybrid intelligent control method has high accuracy and robustness.