论文部分内容阅读
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。
In the brazing production, the third stage heating temperature of the brazing furnace has the characteristics of large time delay and strong time-varying, and the brazing temperature control is difficult. In order to optimize the brazing temperature, the brazing temperature model must be established and optimized. Based on the Recursive Least Square (RLS) algorithm with variable forgetting factor, the online parameter identification of the first-order temperature-dependent temperature model is studied. The parameters and the delay time of the model are obtained. Based on genetic algorithm (GA), PID parameter optimization of temperature target function is studied. The results show that the optimal objective function can be used to control the overshoot, static error and rise time effectively.