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A Robust Guiding Torque Control Method for Automatic Steering Using LMI Algorithm

机译:一种稳健的引导扭矩控制方法,用于使用LMI算法自动转向

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摘要

The existing path tracking methods usually neglect the effect of the drivers on the steering control. This paper proposes a robust steering control method of human-machine steering torque superposition based on linear matrix inequality (LMI) algorithm. First, the model for solving steering superposition torque introduces the steering system and steering resistance torque model in addition to the vehicle model, which increases the nonlinearity and uncertainty of system, and the human in torque superposition control also increases the external interferences. Therefore, this paper proposes a LMI robust control algorithm to reduce the external interference and the influence of uncertain factors on the system and improve the tracking performance of system, by use of Lyapunov stability theory and Schur complement property to convert the region pole assignment and robust control constraint conditions into LMI convex optimization problem. The next, the nonlinear vehicle dynamics solving model including Fiala tire model, steering column model is established; the nonlinear tire model is linearized by use of affine function, and the steering superposition control law is solved by use of LMI. Then, the union CarSim and Simulink simulation is conducted under different situations to verify the robustness and control performance of control system. Finally, through establishing the hardware-in-the-loop experiment table based on LabVIEW-RT, the effectiveness of control strategy is verified. The test results show that the method solves the model uncertainty and the robustness decrement problem resulting from human intervention, ensuring a good tracking performance, and a stable system at the same time.
机译:现有路径跟踪方法通常忽略驱动器对转向控制的影响。本文提出了一种基于线性矩阵不等式(LMI)算法的人机转向扭矩叠加稳健的转向控制方法。首先,除了车辆模型之外,求解转向叠加扭矩的模型引入了转向系统和转向电阻扭矩模型,这增加了系统的非线性和不确定度,并且人扭矩叠加控制的人也增加了外部干扰。因此,本文提出了一种鲁棒控制算法,以减少外部干扰和不确定因素对系统的影响,提高系统的跟踪性能,利用Lyapunov稳定性理论和Schur补充性转换区域极值分配和强大控制约束条件进入LMI凸优化问题。接下来,建立包括小毛轮胎模型的非线性车辆动力学求解模型,转向柱模型建立;非线性轮胎模型通过使用仿射功能线性化,通过使用LMI来解决转向叠加控制法。然后,联盟Carsim和Simulink仿真在不同的情况下进行,以验证控制系统的鲁棒性和控制性能。最后,通过建立基于LabVIEW-RT的硬件实验表,验证了控制策略的有效性。测试结果表明,该方法解决了人为干预,确保了良好的跟踪性能和稳定的系统,解决了模型不确定性和鲁棒性减少问题。

著录项

  • 来源
    《Quality Control, Transactions》 |2020年第2020期|22162-22169|共8页
  • 作者单位

    Liaocheng Univ Sch Mech & Automot Engn Liaocheng 252059 Shandong Peoples R China;

    Liaocheng Univ Sch Mech & Automot Engn Liaocheng 252059 Shandong Peoples R China;

    Liaocheng Univ Sch Mech & Automot Engn Liaocheng 252059 Shandong Peoples R China;

    Liaocheng Univ Sch Mech & Automot Engn Liaocheng 252059 Shandong Peoples R China;

    Liaocheng Univ Sch Mech & Automot Engn Liaocheng 252059 Shandong Peoples R China;

    Huawei Technol Noahs Ark Lab Beijing 100085 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Steering system; intelligent vehicle; LMI; human-machine co-driving;

    机译:转向系统;智能车辆;LMI;人机共同驾驶;

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