基于遗传算法的PID参数优化在过热蒸汽温度控制中的应用

Wang Jingi, Xuejin Yang, Chen Lei
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引用次数: 8

摘要

针对电厂过热蒸汽温度时滞、惯性大的特点,提出了一种以系统超调量、上升时间和整定时间为性能指标的最优PID控制器。采用实数编码的遗传算法对PID参数进行优化。最后得到一组最优PID参数。仿真结果表明,本文所设计的基于遗传算法的PID控制器在被控对象发生较大变化的情况下仍具有自学习和自适应的能力。当被控对象发生变化时,该控制器具有动态过渡时间短、超调量小、振荡小等特点,能获得理想的控制效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The application of GA-based PID parameter optimization for the control of superheated steam temperature
Aiming at the characteristics as time-delay, large inertia of superheated steam temperature in the power plants, an optimal PID controller which takes the overshoot, rise time and setting time of the system as the performance indicators have been proposed. The PID parameters were optimized by the means of the genetic algorithm with real number encoding. Finally, a group of optimal PID parameters were obtained. Simulation results indicate the GA-Based PID controller in this paper still has the ability of self-learning and adaptive even the controlled object is greatly changed. The controller can acquire an ideal control effect with shorter dynamic transition time, smaller overshoot and oscillation when the controlled object is changing.
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