【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 ,取得了较好的工业应用效果更多还原

【Abstract】 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.更多还原