Journal of Computer Applications ›› 2022, Vol. 42 ›› Issue (5): 1634-1641.DOI: 10.11772/j.issn.1001-9081.2021050745
• Frontier and comprehensive applications • Previous Articles Next Articles
Yanfei LIU(), Zheng PENG, Yihui WANG, Zhong WANG
Received:
2021-05-10
Revised:
2021-09-12
Accepted:
2021-12-21
Online:
2022-03-08
Published:
2022-05-10
Contact:
Yanfei LIU
About author:
LIU Yanfei, born in 1975, Ph. D., professor. His researchinterests include optimum control,embedded system.Supported by:
通讯作者:
刘延飞
作者简介:
刘延飞(1975—),男,陕西咸阳人,教授,博士,主要研究方向:最优控制、嵌入式系统 bbmcu@126.com基金资助:
CLC Number:
Yanfei LIU, Zheng PENG, Yihui WANG, Zhong WANG. PID parameter tuning of brushed direct-current motor based on improved genetic algorithm[J]. Journal of Computer Applications, 2022, 42(5): 1634-1641.
刘延飞, 彭征, 王艺辉, 王忠. 基于改进的遗传算法的有刷直流电机PID参数整定[J]. 《计算机应用》唯一官方网站, 2022, 42(5): 1634-1641.
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URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2021050745
参数 | 值 |
---|---|
电阻 | 0.476 |
电驱电感 | 0.200 |
转矩常数 | 3.87 |
阻尼系数 | 4.16 |
反电动势系数 | 4.00 |
系统转动惯量 | 4.40 |
Tab. 1 Parameters of DC motor
参数 | 值 |
---|---|
电阻 | 0.476 |
电驱电感 | 0.200 |
转矩常数 | 3.87 |
阻尼系数 | 4.16 |
反电动势系数 | 4.00 |
系统转动惯量 | 4.40 |
参数 | 值 |
---|---|
种群大小 | 220 |
进化代数 | 70 |
交叉率 | 0.5 |
变异率 | 0.005 |
(0,5) | |
(0,4) | |
(0,6) |
Tab. 2 Parameters of GA and EIGA
参数 | 值 |
---|---|
种群大小 | 220 |
进化代数 | 70 |
交叉率 | 0.5 |
变异率 | 0.005 |
(0,5) | |
(0,4) | |
(0,6) |
方法 | 上升时间/s | 稳定时间/s | 过冲/% |
---|---|---|---|
AC | 0.176 5 | 1.818 2 | 0.408 6 |
ZN | 2.240 9 | 4.033 6 | 0.067 8× |
CC | 0.515 0 | 2.188 8 | 0.231 5 |
IMC | 0.666 7 | 4.111 1 | 0.078 2 |
GA | 0.012 4 | 0.008 0 | 8.769 4× |
EIGA | 0.008 9 | 0.005 2 | 2.426 2× |
Tab. 3 System response performance under different methods
方法 | 上升时间/s | 稳定时间/s | 过冲/% |
---|---|---|---|
AC | 0.176 5 | 1.818 2 | 0.408 6 |
ZN | 2.240 9 | 4.033 6 | 0.067 8× |
CC | 0.515 0 | 2.188 8 | 0.231 5 |
IMC | 0.666 7 | 4.111 1 | 0.078 2 |
GA | 0.012 4 | 0.008 0 | 8.769 4× |
EIGA | 0.008 9 | 0.005 2 | 2.426 2× |
方法 | |||
---|---|---|---|
AC | 0.158 8 | 0.636 9 | 0.013 2 |
ZN | 0.002 8 | 0.009 0 | 1.067 9 |
CC | 0.034 1 | 0.063 4 | 0.003 7 |
IMC | 0.031 0 | 0.019 0 | 0.001 2 |
GA | 3.565 5 | 3.981 4 | 1.086 9 |
EIGA | 4.824 8 | 3.995 0 | 1.686 8 |
Tab. 4 PID parameters tuned by different methods
方法 | |||
---|---|---|---|
AC | 0.158 8 | 0.636 9 | 0.013 2 |
ZN | 0.002 8 | 0.009 0 | 1.067 9 |
CC | 0.034 1 | 0.063 4 | 0.003 7 |
IMC | 0.031 0 | 0.019 0 | 0.001 2 |
GA | 3.565 5 | 3.981 4 | 1.086 9 |
EIGA | 4.824 8 | 3.995 0 | 1.686 8 |
方法 | 最高适应度值的比例 | ||||
---|---|---|---|---|---|
60% | 90% | 95% | 99% | 100% | |
GA | 7 | 75 | 86 | — | — |
EIGA | 2 | 8 | 18 | 159 | 166 |
Tab. 5 Generation number corresponding to fitness value
方法 | 最高适应度值的比例 | ||||
---|---|---|---|---|---|
60% | 90% | 95% | 99% | 100% | |
GA | 7 | 75 | 86 | — | — |
EIGA | 2 | 8 | 18 | 159 | 166 |
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