A Robust Guiding Torque Control Method for Automatic Steering Using LMI Algorithm
A Robust Guiding Torque Control Method for Automatic Steering Using LMI Algorithm
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DOI：
10.1109/access.2020.2969207
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发表时间：
2020-01-01
期刊：
影响因子：
3.9
通讯作者：
He, Xiangkun
中科院分区：
文献类型：
--
作者：
Bai, Guangtong;Bao, Chunjiang;He, Xiangkun
现有的路径跟踪方法通常忽略驾驶员对转向控制的影响。提出一种基于线性矩阵不等式（LMI）算法的人机转向扭矩叠加的鲁棒转向控制方法。首先，求解转向叠加扭矩的模型除了车辆模型外还引入了转向系统和转向阻扭矩模型，增加了系统的非线性和不确定性，而人为进行扭矩叠加控制也增加了外界干扰。因此，为了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，本文提出一种LMI鲁棒控制算法，利用Lyapunov稳定性理论和Schur补性质将区域极点分配和鲁棒控制约束条件转化为LMI凸优化问题。其次，建立了车辆非线性动力学求解模型，包括Fiala轮胎模型、转向柱模型；利用仿射函数对非线性轮胎模型进行线性化，利用LMI求解转向叠加控制律。然后，结合CarSim和Simulink在不同情况下进行仿真，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的半实物实验表，验证了控制策略的有效性。测试结果表明，该方法解决了模型不确定性和人为干预导致的鲁棒性下降问题，保证了良好的跟踪性能，同时保证了系统的稳定。
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.