Real-time Parameter Updating and Path-following Control for Autonomous Vehicles on Slope Roads
Real-time Parameter Updating and Path-following Control for Autonomous Vehicles on Slope Roads
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DOI：
10.1007/s12555-021-0269-8
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发表时间：
2022-06
期刊：
影响因子：
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通讯作者：
Zhongchao Liang;Yidi Chen;Jing Zhao
中科院分区：
文献类型：
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作者：
Zhongchao Liang;Yidi Chen;Jing Zhao
提出了一种四轮独立驱动（FWID）电动自主地面车辆（EAGV）在斜坡道路上的路径跟踪控制器和转矩分配策略。为了提高控制器的实时性，提出了一种线性参数变模型的模型预测控制（MPC）控制器，以保持车辆的动态稳定性并使EAGV沿着给定的路径运动。通过更新状态参数，该控制器可以最大限度地降低车辆在斜坡路面上的法向轮胎力和重力分量不均匀的影响。通过控制前轮转向角和各轮驱动转矩，可以跟踪车辆横向位置、纵向位置、偏航角和速度的理想轨迹。最后，在CarSim-Matlab平台上进行了高保真仿真，结果表明，基于转矩分配策略的LPV-MPC控制器能够有效地实现控制目标。
This paper proposes a path-following controller and a torque allocation strategy for a four-wheel-independent-drive (FWID) electric autonomous ground vehicle (EAGV) on the slope roads. To improve the real-time accuracy of the controller, a model-predictive-control (MPC) controller with a linear-parameter-varying (LPV) model is proposed to maintain the vehicle dynamic stability and follow the given path for the EAGV. By updating the parameters of the states, the proposed controller can minimize the effects of the unequal normal tire forces and the gravity components of the vehicle on the slope road. As a result, the desired trajectory of the lateral position, longitudinal position, yaw angle, and velocity can be tracked by controlling the front-wheel-steering angle and the driving torque of each wheel. Finally, the high-fidelity simulations have been implemented on the CarSim-Matlab platform, and the results show that the proposed LPV-MPC controller with the torque allocation strategy is effective to achieve the control targets.