带测量噪声干扰的无人驾驶汽车路径跟踪控制  

Path Tracking Control for Autonomous Vehicle with Measurement Noise

作　　者：李雷[1] 贾新春[1] 贾祝融[1] 成婷婷[1] 

机构地区：[1]山西大学数学科学学院,山西太原030006

出　　处：《山西大学学报（自然科学版）》2010年第3期384-387,共4页Journal of Shanxi University(Natural Science Edition)

基　　金：国家自然科学基金(90820014)

摘　　要：提出了一种带有Kalman滤波器的最优预测控制结构,用于无人驾驶汽车的路径跟踪控制.无人驾驶汽车对道路环境与车体状态的感知一般通过GPRS、雷达、摄像机、陀螺仪等获得,测量过程往往带有噪声.带有Kalman滤波的最优预测控制器,与不考虑噪声干扰的最优预测控制器相比,产生比较平滑的控制序列,减少了机械损耗.An optimal preview control structure with Kalman filtering was introduced to the path tracking control for autonomous vehicle.Road environment information and vehicle’s states are obtained usually by utilizing GPRS,radar,camera,gyroscope and so on.This process,however,usually appears noise.Compared to the optimal predictive controller without Kalman filtering,the more smooth control sequence can be generated by the optimal preview controller with Kalman filtering,as well as reducing mechanical loss.

关 键 词：无人驾驶汽车 KALMAN滤波 预测控制 路径跟踪 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]