[1]兰靛靛,甘达,林鸿森,等.粒子群算法优化的车辆悬架座椅模糊PID控制[J].华侨大学学报(自然科学版),2025,(1):23-29.[doi:10.11830/ISSN.1000-5013.202405020]
　LAN Diandian,GAN Da,LIN Hongsen,et al.Fuzzy PID Control of Vehicle Suspension Seat Optimized by Particle Swarm Algorithm[J].Journal of Huaqiao University(Natural Science),2025,(1):23-29.[doi:10.11830/ISSN.1000-5013.202405020]
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粒子群算法优化的车辆悬架座椅模糊PID控制()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
期数:
2025年第1期
页码:
23-29
栏目:
出版日期:
2025-01-10

文章信息/Info

Title:
Fuzzy PID Control of Vehicle Suspension Seat Optimized by Particle Swarm Algorithm
文章编号:
1000-5013(2025)01-0023-07
作者:
兰靛靛1; 2;  甘达1;  林鸿森3;  林祖胜1; 2
1. 厦门理工学院 机械与汽车工程学院, 福建 厦门 361024;2. 厦门理工学院 福建省客车先进设计制造重点实验室, 福建 厦门 361024;3. 厦门国创中心 先进电驱动技术创新中心, 福建 厦门 361006
Author(s):
LAN Diandian1; 2;  GAN Da1;  LIN Hongsen3;  LIN Zusheng1; 2
1. School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361024, China; 2. Fujian Key Laboratory of Bus Advanced Design and Manufacture, Xiamen University of Technology, Xiamen 361024, China; 3. Advanced Electric Drive Technology Innovation Branch, Xiamen National Innovation Center, Xiamen 361006, China
关键词:
悬架座椅;  粒子群算法;  模糊PID控制;  硬件在环仿真试验
Keywords:
suspension seat;  particle swarm algorithm;  fuzzy PID control;  hardware-in-the-loop test
分类号:
U461.4
DOI:
10.11830/ISSN.1000-5013.202405020
文献标志码:
A
摘要:
针对车辆悬架座椅的振动问题,基于ADAMS/View和MATLAB/Simulink平台建立三自由度1/4车辆主动悬架座椅系统模型和路面模型,提出一种运用粒子群算法优化模糊PID的控制方法。该方法融合标准粒子群算法与模糊PID算法,通过粒子群算法对模糊PID控制中的量化因子、比例因子和模糊规则参数进行优化,解决模糊PID控制参数的选取存在经验性和主观性的问题。仿真结果表明:在不同的车速下,相较于模糊PID控制,粒子群优化模糊PID控制的座椅加速度下降16.5%以上,相较于被动悬架座椅,粒子群优化模糊PID控制的座椅加速度下降48.0%以上,减振效果改善明显。
Abstract:
Aiming at addressing the vibration problem of vehicle suspension seat, a three-degree-of-freedom 1/4 vehicle active suspension seat system model and a road profile model were established based on ADAMS/View and MATLAB/Simulink platforms, and a control method using particle swarm algorithm to optimize fuzzy PID was proposed. This method integrates the standard particle swarm algorithm with the fuzzy PID algorithm, optimizing the quantization factor, scale factor and fuzzy rule parameters in the fuzzy PID control through the particle swarm algorithm, to solve the problem of empirical and subjective selection of the fuzzy PID control parameters. The simulation results indicate that, under different vehicle speeds, the seat acceleration using particle swarm optimized fuzzy PID control is reduced by more than 16.5% compared to fuzzy PID control, and by over 48.0% compared to passive suspension seats, thereby significantly enhancing the damping effect.

参考文献/References:

[1] 刘杉,孙琦,侯力文,等.基于加速粒子群的车辆座椅悬架最优控制研究[J].噪声与振动控制,2018,38(3):49-54,59.
[2] TSENG H E,HROVAT D.State of the art survey: Active and semi-active suspension control[J].Vehicle System Dynamics,2015,53(7):1034-1062.DOI:10.1080/00423114.2015.1037313.
[3] LI Weixing,DU Haiping,NING Donghong,et al.Event-riggered H∞ control for active seat suspension systems based on relaxed conditions for stability[J].Mechanical Systems and Signal Processing,2021,149:1-15.DOI:10.1016/j.ymssp.2020.107210.
[4] GAN Zhengkang,ANDREW J H,DARLING J.Adaptive control of an active seat for occupant vibration reduction[J].Journal of Sound and Vibration,2015,349:39-55.DOI:10.1016/j.jsv.2015.03.050.
[5] 于曰伟,赵雷雷,周长城,等.车辆座椅次优控制主动悬架设计及分析[J].北京邮电大学学报,2021,44(3):87-93.DOI:10.13190/j.jbupt.2020-219.
[6] SHI Hongyan,PAN Shouli,LIU Liping,et al.Research on active suspension control strategy based on fuzzy PID control[J].Hydrome-Chatronic Engineering,2015,43(24):67-74.
[7] 袁传义,张焱,唐金花.强横风作用下车辆半主动悬架模糊PID控制研究[J].噪声与振动控制,2022,42(3):168-171,236.
[8] 胡启国,杨晨光.考虑路面时变的整车主动悬架的改进模糊PID集成控制策略[J].现代制造工程,2020,2:20-25.
[9] 冯金芝,喻凡,郑松林,等.基于遗传算法的主动油气悬架分成控制[J].上海交通大学学报,2014,48(4):525-531.
[10] 马克,米林,谭伟,等.基于FPGA的汽车主动悬架模糊自适应PID控制器设计[J].机床与液压,2018,46(2):95-99,148.DOI:10.3969/j.issn.1001-3881.2018.14.027.
[11] 赵家豪,魏民祥,丁玉章,等.增程式APU混沌退火混合粒子群优化模糊PID动态控制[J].航空动力学报,2021,36(6):1213-1221.DOI:10.13224/j.cnki.jasp.2021.06.010.
[12] BOUKHALFA G,BELKACEM S,GHIKHI A,et al.Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor[J].Journal of Central South University,2019,26(7):1886-1896.DOI:10.1007/s11771-019-4142-3.
[13] 李扬,候加林,苑进,等.基于改进PSO的模糊PID高枝修剪机械臂末端抑振算法与试验[J].农业工程学报,2017,33(10):49-58.DOI:10.11975/j.issn.1002-6819.2017.10.007.
[14] 余志生.汽车理论[M].6版.北京:机械工业出版社,2018.
[15] EBERHART R C,KENNEDY J.A new optimizer using particle swarm theory[C]//Proceedings of the Sixth International Symposium on Micro Machine and Human Science.Piscataway:IEEE Service Center,1995:39-43.
[16] SHI Yuhui,EBERHART R C.A modified particle swarm optimizer[C]//Proceedings of the IEEE Congress on Evolutionary Computation.Piscataway:IEEE Service Center,1999:69-73.
[17] 周嗣理,李国丽,王群京,等.基于改进粒子群优化算法的永磁球形电机驱动策略研究[J].电工技术学报,2023,38(1):166-176,189.DOI:10.19595/j.cnki.1000-6753.tces.210841.
[18] INTERNATIONAL ORGANIZATION FOR STANDARDIZATION.Mechanical vibration and shock human exposure to whole-body vibration-part 1: General recuirements: ISO 2631-1-1997[S].Geneva:International Organization for Standardization,1997.

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备注/Memo

备注/Memo:
收稿日期: 2024-05-29
通信作者: 兰靛靛(1970-),女,高级工程师,主要从事振动噪声控制的研究。E-mail:Landd10@163.com。
基金项目: 福建省自然科学基金资助项目(2021J011199)https://hdxb.hqu.edu.cn/
更新日期/Last Update: 2025-01-20