中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

Journal of Chongqing Jiaotong University(Natural Science) ›› 2020, Vol. 39 ›› Issue (11): 128-135.DOI: 10.3969/j.issn.1674-0696.2020.11.19

• Vehicle &Electromechanical Engineering • Previous Articles     Next Articles

Optimal Control of Hydraulic Active Lateral Stabilizer of Vehicle Based on Kalman Filter

ZHAO Qiang, SUN Zhu   

  1. (School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, Heilongjiang, China)
  • Received:2019-08-09 Revised:2019-11-14 Online:2020-11-19 Published:2020-11-23

基于卡尔曼滤波的车辆液压主动横向稳定杆最优控制研究

赵强,孙柱   

  1. (东北林业大学 交通学院,黑龙江 哈尔滨 150040)
  • 作者简介:赵强(1971—),男,黑龙江富锦人,教授,博士,博士生导师,主要从事车辆动力学方面的研究。E-mail:zhaoqiangmvp@163.com 通信作者:孙柱(1996—),男,山东新泰人,硕士研究生,主要从事车辆动力学方面的研究。E-mail: 203887899@qq.com
  • 基金资助:
    黑龙江省留学归国人员科学基金项目(LC2015019)

Abstract: Firstly, the vehicle dynamics model and the active stabilizer actuator model of the hydraulic cylinder controlled by the electro-hydraulic servo valve were established. Then the space model of the system state was derived. Thirdly, Kalman filter algorithm was used to make an optimal estimation of the centroid side-slip angle at centre of mass, yaw rate, sprung mass roll angle, sprung mass roll angular velocity, etc. Based on the optimal estimation, an optimal feedback matrix was designed by using Riccati equation to realize the optimal control of LQG. Furthermore, the simulation verification was carried out in MATLAB/Simulink and compared with the passive transverse stabilizer. The results show that the designed LQG optimal control method has an obvious effect in restraining body roll and can effectively improve vehicle roll stability.

Key words: vehicle engineering, active transverse stabilizer, roll stability, Kalman filtering, LQG control

摘要: 通过建立整车动力学模型和电液伺服阀控制液压缸主动稳定杆作动器模型,推导得出系统状态的空间模型;采用卡尔曼滤波算法对质心侧偏角、横摆角速度、簧上质量侧倾角、簧上质量侧倾角速度等进行最优估计;并基于最优估计值,采用黎卡提方程设计了一个最优反馈阵,实现了LQG的最优控制。并在MATLAB/Simulink中进行仿真验证,并与被动横向稳定杆进行比较。结果表明:所设计的LQG最优控制算法在抑制车身侧倾效果明显,能有效提高车辆侧倾稳定性。

关键词: 车辆工程, 主动横向稳定杆, 侧倾稳定性, Kalman滤波, LQG控制

CLC Number: