遗传算法在电石炉系统PID参数优化中的应用

Application of Genetic Algorithm in PID Parameters Optimization in CaC_2 Furnace System

针对电石炉控制系统的特点,设计出一种最优PID控制器。该控制器以系统响应的超调量、上升时间及调节时间为性能指标,利用遗传算法通过对PID参数进行实数编码、选择合适的适应度函数、自适应的交叉概率和变异概率,对PID控制器的参数进行了优化,最终得到一组PID参数的最优值。对比仿真试验的结果表明,设计出的最优PID控制器性能优于常规的PID控制器。这种最优PID控制器用于电石炉控制系统中可达到良好的动态性能和鲁棒性能。

Aiming at the characteristics of the Calcium Carbide （ CaC2 ） furnace control system, an optimal PID controller has been designed. By taking the overshoot, rise time, and setting time of system response as the performance indexes, and by means of the genetic algorithm with real number encoding, appropriate fitness function, adaptive crossover, and mutation probability, the PID parameters were optimized. Finally, a group of optimal PID parameters were obtained. In comparison with simulated experiments, the results show that the performance of the optimal PID controller is better than that of the conventional PID controller. The optimal PID controller offers excellent dynamic performance and robustness in CaC2 furnace control system.