文档介绍：上海交通大学
硕士学位论文
智能车动力学模型参数辨识方法研究
姓名:方兴
申请学位级别:硕士
专业:控制理论与控制工程
指导教师:杨明
20090201
上海交通大学硕士论文摘要
智能车动力学模型参数辨识方法研究
摘要
在行车安全和交通效率问题日益凸显的今天,智能车技术正在快
速发展。为了达到更好的车辆控制效果,期望使用基于动力学的车体
控制方法。但是在车辆动力学模型中,某些参数的确定非常困难或者
测量成本昂贵。为此,本文进行了针对智能车的动力学模型参数辨识
研究。
为了便于智能车动力学模型参数辨识的研究,本文首先搭建了以
智能小车实验平台,该智能小车具备良好的转向特性和速度特性,而
且在结合了嵌入式微控制器、摄像头和测速编码器后能够实现车辆的
自主导航。
然后提出了基于激光雷达的智能小车定位方法,该方法把切线角
度直方图和 XY 直方图的优势进行巧妙结合以进行车辆位姿预估,再
运用基于模板匹配和鲁棒迭代最近点算法(Iterative Closest Point,
ICP)的定位方法对智能小车进行定位,最后使用扩展卡尔曼滤波
(Extended Kalman Filter, EKF)进行位姿跟踪。仿真实验和实际实验
证明,该定位方法具备较好的定位鲁棒性和精度。
此后,基于以上定位结果,进行了智能小车动力学参数辨识的初
II
上海交通大学硕士论文摘要
步研究,在二自由度动力学模型的基础上推导出参数辨识的方法和步
骤,最后基于辨识参数的仿真轨迹与实际的定位轨迹对比,验证了该
辨识方法的可行性。
关键词:智能小车,激光雷达,车辆动力学,定位,辨识
III
上海交通大学硕士论文 ABSTRACT
RESEARCH ON IDENTIFICATION OF
DYNAMIC PARAMETERS FOR INTELLIGENT VEHICLE
ABSTRACT
As the prominence of traffic safety and efficiency, intelligent vehicle
technology develops rapidly. To get the better driving, it’s reasonable to
control based on vehicle dynamics. Unfortunately, some parameters in
dynamic model are difficult to determine or costly to measure. Research
on identification of dynamic parameters for intelligent vehicle is stated in
this paper.
For the convenience of research work, an experiment platform based on
smart vehicle is developed. The smart vehicle performs well in steering
and speed property. After being integrated with embedded
micro-controllers, camera and encoder, it have the ability of autonomous
navigation.
Then a localization method of the smart vehicle based on laser radar is
given. This bines the advantages of tangent angle histogram
IV
上海交通大学硕士论文 ABSTRACT
and XY histogram to pre-estimate the pose. Later, model registration and
robust Iterative Closest Point (ICP) algorithm is designed to locate the
smart vehicle. Finally, pensating laser radar deficiencies,
Extended Kalman Filter (EKF) algorithm is used for Lase