摘要
烧结过程是一个复杂的物理、化学反应过程,存在大滞后性、强非线性、多目标、多约束条件等控制难点。为了实现铁矿石烧结过程中混合料料槽料位和烧结终点这两个关键参数的综合控制,提出了一种基于优先级的协调优化控制方法。首先,通过综合运用神经网络预测和模糊控制,建立烧结终点的智能控制模型;同时,为了稳定混合料料槽料位,分析影响料槽料位的主要因素,基于专家知识建立了混合料料槽料位专家控制模型;然后,通过构造基于优先级的协调优化控制模型,在优先级控制的基础上采用软切换控制,将两个控制器相结合,获得最适宜的速比以及台车速度增量,实现烧结生产过程的协调优化控制。最后,针对该协调控制策略,设计了其工厂实现方案。
Sintering process is a complex physical and chemical reaction process which possesses the characteristics such as large delay, strong nonlinearity and uncertainty, multi-objective and multi-constrained. Burning through point is a key factor during sintering, which affects heat status of sintering process. Bunker-level is related to the sintering safety directly. To optimize these two key parameters of the iron ore sintering process, a coordinated optimal control method is presented based on priority. First, an intelligent control model of the burning through points is established by using neural network predictive and fuzzy control. In addition, based on the analysis on the factors affecting the stability of bunker level, a bunker-level control model is set up according to the experience of the local expert, which can maintain the bunker level and insure the safety of the sintering process. Then, the coordination control model based on priority which takes the soft switch control is designed to combine two different controllers, so that it results in coordinated optimal control of ratio and trolley speed. Finally, an experiment platform system of sinter is designed to realize this coordinated optimal control method.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2016年第3期885-890,共6页
CIESC Journal
基金
国家自然科学基金重大国际合作研究项目(61210011)
湖北省自然科学基金创新群体项目(2015CFA010)~~
关键词
烧结
烧结终点
优化
神经网络
优先级
软切换
sintering
burning through point
optimize
neural network
priority
soft switch