On integrated optimal control system for aluminum powder nitrogen atomizing & classifying process

The production of aluminum powder nitrogen atomizing and classifying is a process with strong nonlinear, coupling, large lag, and uncertainty. It is difficult to achieve global optimal control for atomizing process by using single intelligent or conventional method. In this paper, research work to the techniques features and control demands of the aluminum powder nitrogen atomizing process is done. Using the integrated optimal control technology, a distributed control system is presented to effectively control the aluminum powder nitrogen atomizing process and optimize it. As a result, the temperature of atomizing furnace is stabilizing for melted aluminum atomizing; the concentration of oxygen, pressure and temperature of the recycle nitrogen are all controlled very well; the aluminum powder nitrogen atomization process model based on RBF neural networks is presented and enhanced GA based aluminum powder nitrogen atomizing process integrated optimal control is implemented to improve the atomizing effect of aluminum powder and promote the percentage of super-tiny aluminum powder greatly.