摘要
针对稀土萃取分离生产过程的特点,将机理分析与神经网络技术相结合,给出了实现稀土萃取分离生产过程组份含量在线预测的软测量模型及其校正算法.提出了基于案例推理和软测量技术相结合的稀土萃取分离生产过程智能优化设定控制技术.将该技术应用于某公司HAB双溶剂萃取提钇分离生产过程,实现了萃取分离生产过程的优化控制和优化运行,取得了明显的应用成效.
Due to the characteristics of rare-earth extracting separation process, the mechanism analysis is combined with neural network technology. Online soft sensing model of the component content and the revised algorithm are provided in the rare-earth extracting separation process. The technology of intelligent optimal control for the rare-earth extraction process is introduced. It integrates the case reasoning and the component content soft sensing technology based on neural networks. The technology is applied to a real yttrium extracting separation process by HAB double solvents, realizing the optimal control and running of the extracting separation process.
出处
《控制与决策》
EI
CSCD
北大核心
2005年第4期398-402,407,共6页
Control and Decision
基金
国家"十五"科技攻关项目(2002BA315A)
国家973计划项目(2002CB312201)
国家自然科学基金项目(50474020).
关键词
稀土
串级萃取
神经网络
软测量
案例推理
Intelligent control
Neural networks
Optimal control systems
Process control
Solvent extraction
