基于自适应免疫遗传算法的真空退火炉变参数PID温度控制系统

真空退火炉退火温度的精确控制是一个典型的非线性、大时滞、大惯性、存在强交叉耦合、时变的复杂的控制问题,常规的PID控制器很难实现对退火温度的精确控制.本文以神经网络建立的真空退火炉模型为控制模型,利用自适应免疫遗传算法全局搜索获取最优的可变PID参数的方法,解决了真空退火炉退火温度精确控制的问题;应用结果表明,该温度控制系统优于传统的PID控制系统,并具有良好的可靠性、自适应性和鲁棒性.

PID temperature control system of ariable parameters for vacuum annealing furnace based on adaptive immune genetic algorithm

The accurate annealing temperature control of vacuum annealing furnace is a typical control problem with big nonlinear time-delay inertia, cross-coincidence and complicated time-variety. It is difficult to obtain the accurate control of annealing furnace by PID controller. In this article, the model of vacuum annealing furnace based on neural network is used as the control model, which solves the problem of accurately controlling the vacuum annealing furnace with optimizing variable arguments PID controller by the adaptive immune genetic algorithm. And the result of application shows that this temperature control system is better than the tradition PID control system and has good reliability, adaptability and robustness.