基于带可变遗忘因子的GA和RLS的气体保护钎焊炉温度优化（英文）

Temperature optimization based on GA and RLS with variable forgetting factor for gas protection brazing furnaces

在钎焊生产中,钎焊炉第三阶段加热温度具有大时滞和强时变特点,钎焊温度控制困难。为了优化钎焊温度,必须建立钎焊温度模型并对其进行优化。基于带可变遗忘因子的递推最小二乘法(RLS)研究了一阶时滞温度模型的在线参数辨识,得到了该模型的参数和延迟时间。基于遗传算法(GA),研究了温度目标函数的PID参数优化。结果表明:应用优化的目标函数可使得超调量、静态误差和上升时间等得到很好的控制。

For its time delay and parameter varying,the brazing temperature control is difficult in brazing operations. In order to optimize brazing temperature,the brazing temperature model must be established first. Parameter identification and optimization are effective to establish precise temperature models of brazing furnaces. In this investigation,the online parameter identification on first order delay temperature model was proposed based on recursive least squares algorithm（ RLS） with variable forgetting factor. Through identifying and calculating for first order delay temperature model,the mode parameters and delay time was got. Next,PID parameters optimization for the traditional objective function was implemented based on genetic algorithm（ GA）. The overshoot,static error index and rising time in the third stage of the heating requirements,as a result,can be well controlled under the help of modified objective function.