华南理工大学学报(自然科学版) ›› 2013, Vol. 41 ›› Issue (11): 120-124.doi: 10.3969/j.issn.1000-565X.2013.11.020

• 汽车工程 • 上一篇    下一篇

基于模型预测控制的汽车换道操纵逆问题求解

刘英杰 赵又群   

  1. 南京航空航天大学 能源与动力学院,江苏 南京 210016
  • 收稿日期:2013-04-11 修回日期:2013-06-05 出版日期:2013-11-25 发布日期:2013-10-11
  • 通信作者: 赵又群(1968-),男,教授,博士生导师,主要从事车辆系统动力学研究. E-mail:yqzhao@nuaa.edu.cn
  • 作者简介:刘英杰(1982-),男,博士生,主要从事车辆系统动力学研究.E-mail:ufoliuyingjie@163.com
  • 基金资助:

    国家自然科学基金资助项目(11072106)

Solving of Inverse Dynamics for Lane- Change Steering Maneuver Based on Model Predictive Control

Liu Ying- jie Zhao You- qun   

  1. College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,Jiangsu,China
  • Received:2013-04-11 Revised:2013-06-05 Online:2013-11-25 Published:2013-10-11
  • Contact: 赵又群(1968-),男,教授,博士生导师,主要从事车辆系统动力学研究. E-mail:yqzhao@nuaa.edu.cn
  • About author:刘英杰(1982-),男,博士生,主要从事车辆系统动力学研究.E-mail:ufoliuyingjie@163.com
  • Supported by:

    国家自然科学基金资助项目(11072106)

摘要: 传统的控制方法不适合求解汽车转向换道操纵过程的多约束问题,为此,文中将模型预测控制( MPC) 方法用于求解汽车换道操纵逆动力学问题,以驾驶员对汽车施加的转角输入为控制变量,以最佳轨迹完成障碍物转向避让过程为控制目标,将最优控制问题转化为二次规划问题,并利用有效集法求解.计算结果表明,文中提出的模型预测控制方法在求解复杂和多约束的车辆运行轨迹的最佳转向输入问题时具有潜在的优势,可以成功求解汽车换道操纵逆动力学问题.

关键词: 车辆动力学, 主动安全性, 换道, 模型预测控制, 驾驶员行为

Abstract:

As the traditional control methods are infeasible in dealing with multiple constraints in the lane- changesteering maneuver process,the model predictive control (MPC) method is adopted to solve the inverse dynamics forlane- change steering maneuver.In the investigation,the steering angle input is used as the control variable,theoptimal trajectory to complete the collision avoidance process of lane- change steering maneuver is taken as the con-trol objective,and the optimal control problem is converted into a quadratic programming problem,which is thensolved via the active set method.Simulated results show that the proposed method based on MPC is of potential ad-vantage for calculating the optimal steering input of vehicle trajectory with heavy computational complexity and mul-tiple constraints,and that it is effective in solving the inverse dynamics for the lane- change steering maneuver.

Key words: vehicle dynamics, active safety, lane change, model predictive control, driver behavior