| 基于跟踪误差模型的无人驾驶车辆预测控制方法 |
| |
| 引用本文： | 李培新,姜小燕,魏燕定,周晓军.基于跟踪误差模型的无人驾驶车辆预测控制方法[J].农业机械学报,2017,48(10):351-357. |
| |
| 作者姓名： | 李培新 姜小燕 魏燕定 周晓军 |
| |
| 作者单位： | 浙江大学,中国航天科技集团公司第一研究院,浙江大学,浙江大学 |
| |
| 基金项目： | 航天支撑技术基金项目（E20130116） |
| |
| 摘 要： | 针对无人驾驶车辆的轨迹跟踪问题,在分析车辆运动学模型的基础上,设计了一种基于模型预测控制理论的轨迹跟踪控制方法。首先,将车辆运动学模型进行线性化处理,得到车辆运动学线性跟踪误差模型,该模型可以用来预测车辆的未来行为。其次,利用此跟踪误差模型作为预测模型,应用线性模型预测控制方法,通过优化得到使性能指标最小的控制序列,将控制序列的第一步作用于系统。最后,建立了3种典型的道路试验曲线,并且在基于实时多体动力学软件Vortex搭建的虚拟仿真平台中对轨迹跟踪控制器进行了仿真。仿真结果表明,该控制器可以保证无人驾驶车辆快速且稳定地跟踪参考轨迹,距离偏差和方位偏差都在合理的范围内,且实时性可以达到要求。
|
| 关 键 词： | 无人驾驶车辆 跟踪误差 预测控制 |
| 收稿时间： | 2017/1/17 0:00:00 |
Predictive Control Method of Autonomous Vehicle Based on Tracking-error Model |
| |
| LI Peixin,JIANG Xiaoyan,WEI Yanding and ZHOU Xiaojun.Predictive Control Method of Autonomous Vehicle Based on Tracking-error Model[J].Transactions of the Chinese Society of Agricultural Machinery,2017,48(10):351-357. |
| |
| Authors: | LI Peixin JIANG Xiaoyan WEI Yanding and ZHOU Xiaojun |
| |
| Institution: | Zhejiang University,The First Institute of China Aerospace Science and Technology Corporation,Zhejiang University and Zhejiang University |
| |
| Abstract: | For the trajectory tracking problem of autonomous vehicle, on the basis of analysis of kinematic model of vehicle, a model based predictive control method for autonomous vehicle trajectory tracking was designed. Firstly, a linear error model of vehicle kinematics was obtained by using a successive linearization approach, and it was used to predict the future behavior of the vehicle. Secondly, based on this model, it was possible to get a sequence of optimal control by using the linear MPC method and minimizing the objective function, and the first element of this sequence was applied to the system. Lastly, three typical test trajectories (lane change course, figure eight course and road course) were designed and the tracking controller was tested in the virtual simulation platform. The platform was set up on real-time multi-body dynamics software Vortex and visual rendering software Vega Prime. In order to meet the real-time requirements of the platform, two computers were used for dynamic resolving and visual rendering respectively, and the high level architecture (HLA) was adopted to realize the synchronization and data interaction between Vortex and Vega Prime. Simulation results showed that this controller can track the reference trajectory quickly and stably, the distance error and heading error were in a reasonable range. The refresh rate of Vortex and Vega Prime was stabilized at about 30Hz, the error was within ±0.05Hz, indicating that the controller can meet the real-time requirements of the system. |
| |
| Keywords: | autonomous vehicle tracking error predictive control |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《农业机械学报》浏览原始摘要信息 |
| 点击此处可从《农业机械学报》下载免费的PDF全文 |
|
