摘要
本文针对具有非线性、强耦合、不确定、多约束特性的复杂铅锌密闭鼓风烧结过程 ,采用神经网络模型实现了透气性状态和烧穿点位置预测 ,集成惩罚函数法、基于聚类点的并行变步长网格法和最优保存简单遗传算法 (OMSGA)进行状态整体优化 .算法具有全局收敛性和工业有效性 ,解决了复杂铅锌烧结过程实时智能优化控制问题 。
The complex imperial sintering process possesses strong nonlinear, strong coupling, uncertain and multi constrained features. In the paper, the neural network models are used to predict the permeability and burn through point(BTP), and the penalty function, parallel uneven grid method based on clustering and optimum maintaining simple genetic algorithm (OMSGA) are used to complete optimization of the whole status. The algorithm is globally convergent and industrially effective, resolves the real time intelligent optimal control problem in complex imperial sintering process, and can be applied to practical industrial process with better results.
出处
《信息与控制》
CSCD
北大核心
2004年第4期490-494,499,共6页
Information and Control
基金
国家计委高技术产业化示范工程项目 (计投资 [2 0 0 0 ] 2 498号 )
国家 973计划资助项目 ( 2 0 0 2CB3 12 2 0 0 )
关键词
铅锌烧结过程
惩罚函数法
基于聚类点的并行变步长网格法
最优保存简单遗传算法
lead zinc sintering process
penalty function method
parallel uneven grid method based on clustering
optimum maintaining simple genetic algorithm(OMSGA)
