【摘要】 炉温决策是加热炉智能控制的主要任务之一,常规决策过程需多次迭代求取炉温设定值.迭代过程中收敛因子的选取对收敛速度有较大影响,而常规决策方法的收敛因子一般根据经验选取.基于不同条件下被加热钢坯的焓增与边界热流之差对时间积分成正比关系,本文分别推导并提出了计算收敛因子的汇合法、分化法及汇合-分化联合法.汇合法确定收敛因子时无需进行迭代计算,汇合-分化联合法仅需一次迭代计算.对比分析表明:采用汇合-分化联合法确定收敛因子进行炉温决策,仅需一次迭代计算就可达到较高的精度.更多还原

【Abstract】 The furnace temperature decision is one of the main tasks for intelligent control of the heating furnace.However,the traditional decision-making process requires multiple iterations to obtain the furnace temperature setting value. The selection of the convergence factor in the iterative process has a great influence on the convergence rate,while the convergence factors in traditional decision methods are generally selected based on experience. Based on increase of the heated billet’s enthalpy being directly proportional to the time integral of the boundary heat flux D-value under different conditions,in the present paper,the meeting method,separating method and meeting-separating combination method for calculating convergence factors were deduced and proposed. In process of solving the convergence factor via meeting method,iterative calculation can be avoided,while by using meeting-separating combination method,it only need to iterate for one time. The results showed that a high precision can be obtained after iterating for one time by meeting-separating combination method.更多还原