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论文类型：会议论文

发表时间：2008-07-16

收录刊物：EI、Scopus

页面范围：485-489

摘要：The process of aluminum powder nitrogen atomizing has characteristics of strong nonlinear, strong coupling, large lag, and uncertainty and so on. 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, and integrated optimal control technology 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.