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基于模型预测控制的车辆路径跟踪控制研究

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针对低附着系数、大曲率路面下智能车辆跟踪精度低的问题,设计了一种基于模型预测控制的高精度中低速自适应车辆路径跟踪控制器.首先,根据Pacejka轮胎模型分析轮胎的侧偏特性,对轮胎侧偏角的范围进行约束,限制轮胎侧偏力在线性区域,避免车辆产生侧向滑移.其次,根据车辆跟踪参考路径的曲率大小,自适应地调整预测范围内车辆与参考路径的方向偏差权重、横向偏差权重,减小车辆路径跟踪误差.仿真结果表明,本研究所设计的控制器在湿滑的弯道路面下中低速行驶具有较高的跟踪精度.
Vehicle Path Tracking Control Based on Model Predictive Control
Aiming at the problem of low tracking accuracy of intelligent vehicles under low adhesion coef-ficient and large curvature road surface,a high-precision medium-low speed adaptive vehicle path track-ing controller based on model predictive control is designed.Firstly,the lateral deflection characteristics of tires are analyzed according to the Pacejka tire model,and the range of tire lateral deflection angle is constrained to limit the tire lateral deflection force in the linear region to prevent the vehicle from gener-ating lateral slip.Secondly,according to the curvature magnitude of the vehicle tracking reference path,the directional deviation weights,lateral deviation weights of the vehicle and the reference path within the prediction range are adaptively adjusted to reduce the vehicle path tracking error.The results of the simulations demonstrate that the proposed controller exhibits high tracking accuracy,especially when navigating on slippery curved road surfaces at low and medium speeds.

intelligent vehiclespath trackingmodel predictive controlside deviation angle constraints

周骏、韩超

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安徽工程大学电气工程学院,安徽芜湖 241000

智能车辆 路径跟踪 模型预测控制 侧偏角约束

2024

安徽工程大学学报
安徽工程大学

安徽工程大学学报

影响因子:0.289
ISSN:2095-0977
年,卷(期):2024.39(5)