基于遗传算法的贮液缸液位PID控制参数整定

目的在啤酒灌装过程中,贮液缸内液位的变化会直接影响啤酒的质量和产量,而对液位控制的准确、稳定与否,关键在对PID参数的选择。方法针对在贮液缸液位控制调试过程中PID参数选择的盲目性等问题,采用遗传算法对PID参数进行整定,并与临界比例度法整定的结果进行比较。结果经过遗传算法整定的PID参数,其输出响应曲线上升最短时间为3.98 s,超调量最小可达1.9%,调整最短时间为2.23 s。经过比例度法整定的PID参数,其输出响应曲线上升最短时间为1.92 s,超调量最小达23.7%,调整最短时间为11.62 s。结论采用遗传算法整定的PID控制参数总体效果较好,其输出响应曲线上升时间为3.98 s,超调量最小可达4.2%,调整最短时间为2.23 s,满足控制要求。

Tuning of PID Control Parameter for Liquid Level of Liquid Storage Cylinder Based on Genetic Algorithm

Objective In the beer filling process, changes of tank position will directly affect the quality and yield of beer. The key for the accuracy and stability of level control lies in the choice of PID parameters. Methods Targeting at the blindness problem of parameter selection for PID during the debugging process of the liquid storage tank liquid level, genetic algorithm was used for tuning the parameters of PID and the results were compared with the tuning results of the critical ratio method. Results The results showed that after tuning the PID parameters by the genetic algorithm, for the output response curve, the shortest rise time was 3.98 s, the minimum overshoot was 1.9% , and the shortest time of adjustment is 2.23 s. However, after tuning the PID parameters by the critical ratio method, the rise in the shortest time is 1.92 s, the minimum overshoot is 23.7%, and the shortest adjustment time was 3.98 s. Conclusion The overall result of the PID control parameter tuning based on genetic algorithm was better. For the output response curve, the shortest rise time was 3.98 s, the minimum overshoot was 4.2%, and the shortest adjustment time was 2.23 s, which met the control requirements.