匹配驾驶经验的无人驾驶PID车速增长增益控制研究  

Research on Speed Increase Gain Control of Unmanned PID Matching Driving Experience

作　　者：孔菊萍 Kong Juping(Department of Mechanical and Electrical Engineering,Jiangsu Gaochun Secondary Professional School,Gaochun Jiangsu 211301,China)

机构地区：[1]江苏省高淳中等专业学校机电系,江苏高淳211301

出　　处：《现代工业经济和信息化》2025年第3期99-101,共3页Modern Industrial Economy and Informationization

摘　　要：以传统PID方法调节车速,面临着跟踪精度偏低以及需要频繁切换动力与制动模式的情况,容易引起控制量的大幅波动并发生制动力的突变。根据模糊控制开发了一种车速跟踪模型,根据驾驶经验构建模糊控制策略能够避免制动力突变。实时系统仿真测试结果表明:传统PID制动控制量介于0~1.4 MPa,呈现频繁波动的特点;而采用模糊控制制动控制算法则获得了较小波动的制动控制量,形成了变化幅度很小的控制量,实现理想的控制性能。该研究有助于提高车速跟踪精度以及乘坐舒适性,起到汽车行驶节能效果。The traditional PID method is faced with low tracking accuracy and frequent switching of power and braking modes,which is easy to cause large fluctuations of control quantity and sudden change of braking force.A speed tracking model is developed based on fuzzy control,and a fuzzy control strategy based on driving experience can avoid braking force abrupt change.The real-time system simulation test results show that the braking control quantity of traditional PID braking control is between 0~1.4 MPa,which shows the characteristics of frequent fluctuation.The fuzzy control control algorithm is used to obtain the brake control quantity with small fluctuation,form the control quantity with small variation range,and achieve the ideal control performance.The research is helpful to improve the speed tracking accuracy and ride comfort,and play an energy-saving role in vehicle driving.

关 键 词：无人驾驶 驾驶经验 车速跟踪 模糊控制 

分 类 号：U461[机械工程—车辆工程]