考虑侧倾的无人车NMPC轨迹跟踪控制研究
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南京林业大学

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TP273

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Trajectory Tracking Control for Automated Vehicle based on NMPC considering Vehicle Rolling Motion
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Nanjing Forestry University

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    摘要:

    针对高速行驶工况下,无人车转弯时的侧倾,导致车辆模型非线性程度增加,引起轨迹跟踪精度下降和状态失稳的问题,设计了一种考虑车辆侧倾因素,基于非线性模型预测控制(NMPC)的无人车轨迹跟踪控制器,根据拉格朗日分析力学和车辆运动学,考虑车辆侧倾几何学和载荷转移效应,建立了考虑侧倾因素的非线性车辆模型,包括车体动力学模型和修正的“Magic Formula”轮胎模型,基于此车辆模型构建了非线性模型预测控制器(NMPC)的预测模型,并设定了控制器的线性、非线性约束,保证车辆的运动状态处于稳定区域内,在Carsim和Simulink联合仿真平台上,验证了车辆高速蛇形工况和双移线工况下的轨迹跟踪控制效果,仿真结果显示本文设计的控制器有效改善了高速弯道工况下的跟踪精度和车辆状态稳定性。

    Abstract:

    The roll of an autonomous vehicle during a fast-turning process can significantly increase the inherent nonlinear dynamics, and consequently lead to an obvious decrease of trajectory tracking accuracy and stability. A trajectory tracking controller based on a nonlinear model predictive control (NMPC) considering vehicle rolling motion is thus developed for addressing this critical issue in practice. With Lagrangian analytical mechanics and vehicle dynamics analysis methods, nonlinear vehicle models considering roll factors is established, including vehicle body dynamics model and a modified "Magic Formula" tire model. Based on this novel vehicle model, a Nonlinear Model Predictive Controller (NMPC) is constructed, and the linear and nonlinear constraints of the controller are ensured such that the motion of the vehicle is within the stable region. Based on the joint simulation platform of Carsim and Simulink, the trajectory tracking control effect in high-speed serpentine motion and double-shift line motion is verified. Simulation results show that the controller designed in this paper effectively improves the tracking accuracy and vehicle state stability in high-speed turning situations.

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  • 收稿日期:2021-06-10
  • 最后修改日期:2021-08-29
  • 录用日期:2021-09-10
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