基于随机模型预测控制的自主车辆转向控制

王秋; 曲婷; 陈虹

doi:10.13976/j.cnki.xk.2015.0499

基于随机模型预测控制的自主车辆转向控制

王秋¹,
曲婷²,
陈虹^1,2, ,

1.
吉林大学汽车仿真与控制国家重点实验室, 吉林长春 130022
2.
吉林大学通信工程学院, 吉林长春 130022

基金项目: 国家自然科学基金重大研究计划集成项目（91220301）；国家973课题资助项目（2012CB821202）

详细信息

作者简介:
王秋（1989-），女，硕士生．研究领域为随机模型预测控制．
曲婷（1982-），女，博士生．研究领域为随机模型预测控制，驾驶员模型等．
陈虹（1963-），女，博士生导师，教授．研究领域为预测控制，鲁棒控制，非线性控制和汽车控制．

通讯作者:
陈虹，chenh@jlu.edu.cn

中图分类号: TP182
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- 文章访问数: 1494
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出版历程
- 收稿日期: 2014-10-30
- 修回日期: 2015-05-20
- 发布日期: 2015-08-19

Steering Control of Autonomous Vehicles Based on Stochastic Model Predictive Control

WANG Qiu¹,
QU Ting²,
CHEN Hong^1,2, ,

1.
State Key Laboratory of Automotive Simulation and Control, Jinlin University, Changchun 130022, China
2.
College of Comanuni Cation Engineering, Jinlin University, Changchun 130022, China

摘要

摘要: 车辆系统实际存在的诸多不确定性因素会对控制器的性能产生严重影响．首先在传统自行车模型的基础上，充分考虑模型简化过程中可能产生的未建模动态，建立考虑未建模动态的车辆二自由度模型；其次根据随机模型预测控制算法设计转向控制器，实现对车辆侧向轨迹的跟踪．为证明该算法的有效性，结合车辆动力学软件veDYNA在车辆运行的各种工况下进行仿真研究，都实现了较好的跟踪效果．为进一步验证建模过程中考虑的未建模动态的影响，设计了两个控制器并做了一系列的实验，结果表明对车辆的非线性进行补偿可以提高轨迹跟踪的精度．
- 未建模动态 /
- 随机模型预测控制（SMPC） /
- 轨迹跟踪
Abstract: Numerous uncertainty factors in vehicle systems adversely affect the performance of the vehicle steering controller. To rectify this problem, we present a number of counter measures. First, a two-degree-of-freedom vehicle model is proposed; this model is based on the traditional bicycle model and considers possible unmodeled dynamics resulting from simplification of the bicycle model. Then, a steering controller that uses the stochastic model predictive control (SMPC) algorithm is designed to track lateral trajectory. To verify the effectiveness of the proposed algorithm, we perform simulations under various vehicle running conditions using the vehicle dynamics software (veDYNA). The simulation results show that the controller can achieve perfect tracking. To further verify the effects of considering unmodeled dynamics in the model, two controllers are designed and a series of experiments are conducted. The results suggest that the compensation for nonlinear motion can improve the accuracy of trajectory tracking.
- unmodeled dynamics /
- stochastic model predictive control (SMPC) /
- trajectory tracking

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参考文献(20)

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文章访问数: 1494
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基于随机模型预测控制的自主车辆转向控制

通讯作者: 陈虹，chenh@jlu.edu.cn

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Steering Control of Autonomous Vehicles Based on Stochastic Model Predictive Control

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出版历程

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通讯作者:
陈虹，chenh@jlu.edu.cn