A Intelligent Control Model of Hot Metal Desulphurization Process
In view of the shortcomings that traditional desulphurization control models low precision and low auto-adapted ability, according to the mechanism of hot metal desulphurization process, the intelligent control model based on RBF nerve network and feedback consumption control method is introduced. The model uses RBF nerve work technology to build desulphurization control model, uses feedback compensation method to solve model failure problem caused by desulphurization powder quality change. The emulate contrast shows the mathematical model can suffice for the requirement of desulphurization control, can reduce consumption of desulphurization powder effectively. This is the paper style requirement for the Chinese Control and Decision Conference. The writers of papers should and must provide normalized electronic documents in order for readers to search and read papers conveniently.
desulphurization RBF nerve network ant colony algorithm dichotomy method
Zhang Yong Wang Yukun Wang Jiesheng
School of Electronic and Information Engineering, Liaoning University of Science and Technology Anshan 114051
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
3277-3280
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）