高速成像系统中光圈电机的PI参数智能优化算法研究与应用

Research and Application of PI Parameter Intelligence Optimization Algorithm for Aperture Motor in High Speed Imaging System

高速成像系统在断路器线圈故障诊断中的良好效果得到人们的关注,但在检测过程中发现成像系统中光圈电机控制存在精度难以满足现场测试的问题,且PI参数调整繁琐。针对上述问题,本文提出电机控制系统PI参数自动寻优,得到系统PI参数的最优解,从而实现光圈电机的准确、自动控制。本文在传统基因遗传算法基础上,在选择算子、交叉算子以及变异算子的设计上,较传统的SGA做了改进。改进后算法以Schaffer函数求极值问题作为优化测试对象,在平均最佳适应度、平均适应度计算次数以及平均进化代数等指标上均得到改善。并提出IITAE2作为适应度评价方法,对PI参数进行优化。基于IITAE2算法,分别从仿真与实验的角度进行验证,结果表明IITAE2指标遗传算法优化效果更好,可获得性能更优良的PI参数。

Due to its many advantages, the traditional PID strategy has been the dominant control method in the field control. One of the key issues of PID control is the PID parameters tuning and optimization, which is always a tedious trial-and-error procedure. To reduce the number of fitness calculation, the SGA was im- proved, and Schaffer function was taken as an example to verify the effectiveness of the improved SGA pro- posed in this paper. Three fitness evaluation methods were proposed to analyze the parameters optimization results. Both the simulation and experimental results show that the control system using PID parameters opti- mized by IITAE2 has better dynamic performance, which verify the algorithm proposed in this paper.