现代制造工程Issue(11)：48-56,9.DOI:10.16731/j.cnki.1671-3133.2025.11.007
基于视觉的局部优化模糊PID控制策略
Vision-information-based local optimization fuzzy PID control strategy
摘要
Abstract
Traditional suspension systems can only mitigate vibrations after the vehicle receives road excitation,suffering from the drawbacks of an inability to proactively adapt to road condition changes in advance and time delays in the actuation of suspension actuators.To address these issues,a vision-based locally optimized fuzzy PID control strategy is proposed.Firstly,a visual recog-nition module,a road excitation module,and a communication platform are established.Subsequently,leveraging the information from road surface identification,transmission,and fusion,a vision-based locally optimized fuzzy PID control strategy is designed.Finally,through simulation modeling,the performance of different vehicle control strategies is validated under four dis-tinct road excitation scenarios,including Class C and Class D road surfaces,as well as combinations of single and multiple speed bumps.The results demonstrate that,compared to passive suspension,PID control,and fuzzy PID control strategies,the pro-posed vision-based locally optimized fuzzy PID control strategy reduces the vertical acceleration RMS of the vehicle body by 32.4％,23.4％,and 11.7％,respectively,under Class C road excitation with a single speed bump;by 32.4％,21.9％,and 8.1％,respectively,under Class D road excitation with a single speed bump;by 32.2％,23.4％,and 10.8％,respectively,under Class C road excitation with multiple speed bumps;and by 31.0％,21.4％,and 7.4％,respectively,under Class D road excitation with multiple speed bumps.关键词
视觉信息/随机路面激励模型/视觉信息调节控制Key words
visual information/stochastic pavement excitation model/visual information regulation and control分类
交通工程引用本文复制引用
陈哲明,刘岩松,杨鑫,刘国栋..基于视觉的局部优化模糊PID控制策略[J].现代制造工程,2025,(11):48-56,9.基金项目
重庆市教育委员会科学技术研究计划青年项目资助项目(KJQN202101143) （KJQN202101143）
