自动驾驶汽车路径跟踪控制方法研究综述  

A Review of Path Tracking Control Methods for Autonomous Vehicles

作　　者：黄榕 查云飞 Huang Rong;Zha Yunfei(Fujian University of Technology,Fuzhou 350118)

机构地区：[1]福建理工大学,福州350118

出　　处：《汽车文摘》2025年第4期23-28,共6页Automotive Digest

摘　　要：通过对PID控制、鲁棒控制、滑模控制和模型预测控制进行综述,分析了各方法在自动驾驶中的应用特点。PID控制实现简单,但在复杂环境下表现有限;鲁棒控制能处理不确定性和干扰,但设计偏保守;滑模控制响应迅速且抗扰动强,却可能导致抖振问题;模型预测控制提供精确轨迹优化,计算资源需求高。研究表明,PID适合简易环境,鲁棒控制用于稳定性要求高的场合,滑模控制应对快速调整任务,模型预测控制适用于需要高精度的场景。未来研究将聚焦于多策略融合提升性能,适应不同工况,确保稳定性和精度;开发高效实时算法,结合机器学习增强自适应性及提高控制效率和可靠性,实现精准路径跟踪。Through the literature review of PID control,robust control,sliding mode control and model predictive control,the characteristics of each method’s application in autonomous driving are analyzed.PID control is simple to implement but limited in complex environments.Robust control can deal with uncertainty and interference,but the design tends to be conservative.Sliding mode control offers rapid response and strong resistance to disturbances,yet it may cause chattering issues.Model predictive control provides precise trajectory optimization which requires high computational resources.The study shows that PID control is suitable for simple environments,robust control is suitable for situations requiring high stability,sliding mode control is applied to tasks that require for rapid adjustments,and model predictive control is suitable for scenarios that demand high precision.Future research will focus on integratiing multi-strategy to improve performance,adapt to various working conditions,and ensure stability and accuracy.Moreover,it is also necessary to develop efficient real-time algorithms,combine machine learning to enhance adaptability,improve control efficiency and reliability,and achieve accurate path tracking.

关 键 词：路径跟踪 模型预测控制 滑模控制 鲁棒控制 

分 类 号：U471.15[机械工程—车辆工程]