首页|基于转向模式切换的三轴独立转向车辆路径跟踪控制研究

基于转向模式切换的三轴独立转向车辆路径跟踪控制研究

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三轴独立转向车辆广泛应用于特种领域,并逐渐向无人化、智能化发展,路径跟踪控制方法是其中的重要研究内容.三轴独立转向车辆相较于传统车辆具有更加复杂的转向行为,因此在路径跟踪控制过程中需要充分的考虑其转向特性带来的影响.针对三轴独立转向无人车辆在路径跟踪过程中的转向控制问题,基于理论力学和轮胎魔术公式建立多自由度模型,对比不同转向模式下横向位移和横摆角变化差异.然后,以实车响应数据作为参考,采用非支配排序遗传算法Ⅱ(Non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)优化多自由度模型参数,并通过模型仿真获取数据集.通过BP神经网络(Back-propagation network)制定转向模式切换策略,最终将模式切换策略引入模型预测控制器,仿真试验和实车试验结果表明,三轴独立转向车辆在路径跟踪过程中通过转向模式切换可以有效提高跟踪精度.
Research on Three-axis Independent Steering Vehicle Path Tracking Control Based on Steering Mode Switching
Three axle independent steering vehicles are widely used in special fields and are gradually developing towards unmanned and intelligent,with path tracking control methods being an important research content.Three axle independent steering vehicles have more complex steering behaviour compared to traditional vehicles,so it is necessary to fully consider the impact of their steering characteristics in the path tracking control process.This study focuses on the steering control problem of a three axis independent steering unmanned vehicle during path tracking.A multi degree of freedom model is established based on theoretical mechanics and tire magic formulas,and the differences in lateral displacement and yaw angle changes under different steering modes are compared.Then,using the actual vehicle response data as a reference,the non dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)was used to optimize the multi degree of freedom model parameters,and the dataset was obtained through model simulation.The steering mode switching strategy is developed through the BP neural network,and finally the mode switching strategy is introduced into the model predictive controller.Simulation and actual vehicle test results show that the tracking accuracy of three-axis independent steering vehicles can be effectively improved through steering mode switching during the path tracking process.

three-axis vehicleindependent steeringmode switchneural networkpath tracking

张昊、魏超、胡纪滨、陈泳丹

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北京理工大学机械与车辆学院 北京 100081

中国北方车辆研究所 北京 100072

三轴车辆 独立转向 模式切换 神经网络 路径跟踪

国家自然科学基金资助项目

U1764257

2024

机械工程学报
中国机械工程学会

机械工程学报

CSTPCD北大核心
影响因子:1.362
ISSN:0577-6686
年,卷(期):2024.60(2)
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