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匹配驾驶经验的无人驾驶PID车速增长增益控制研究
孔菊萍 2025/5/19 16:53:16
江苏省高淳中等专业学校，机电系，江苏高淳 211301
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制动控制制动控制量介于0～1.4MPa，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，实现了理想的控制性能。该研究有助于提到车速跟踪精度以及乘坐舒适性，起到汽车行驶节能效果。
关键词：无人驾驶；驾驶经验；车速跟踪；模糊控制
中图分类号：U461
Research on speed increase gain control of unmanned PID matching driving experience
Kong Juping
Department of Mechanical and Electrical Engineering, Jiangsu Gaochun Secondary Professional School, Gaochun 21130, China
Abstract: 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 ~ 1.4MPa, 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.
Key words: unmanned driving; Driving experience; Speed tracking; Fuzzy control
0 引言
随着汽车产业规模的迅速扩大，车辆数量急剧增加，对交通管控安全、能源消耗都造成了极大压力，这也为促进汽车产业的绿色发展与智能化技术开发指出了新的发展思路，需要进一步开发更加绿色、环保、节能的汽车技术[1-2。针对无人驾驶汽车进行技术开发时需要解决的一个关键问题是确保对车辆进行运动状态的精确平稳控制[3]。
相关方面的研究吸引了很多的学者，取得了一定的研究成果。文献[4]则根据系统辨识过程建立车辆纵向运动模型，再根据上述动力模型构建了相应的控制方案，有效避免系统模型参数偏差与外部扰动引起的结果偏差。文献[5]采用自适应控制的方法确定了符合驾驶员操控习惯的纵向控制方法，能够在确保车速跟踪精度满足要求的基础上获得更优的舒适度。
随着越来越多学者对智能车辆的纵向车速开展研究，关于车辆控制的人员习惯与驾驶员对油门与制动器控制时的行为特征也引起了人们更加高度的（未完，下一页）
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