基于PIDSM-AF的智能车辆横向控制研究
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作者单位:

南京林业大学 汽车与交通工程学院

中图分类号:

U463.6

基金项目:

江苏省产业前瞻与关键核心技术项目(BE2022053-2)


Research on lateral control of intelligent vehicles based on PIDSM-AF
Author:
Affiliation:

College of Automobile and Traffic Engineering,Nanjing Forestry University

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    摘要:

    路径跟踪精度是智能车辆安全自主行驶的基础。为解决滑模控制系统的抖振问题,提高路径跟踪控制器的控制精度,提出了一种引入激活函数的积分滑模控制策略(PIDSM-AF)。首先,以二自由度车辆模型为基础,将车辆的动力学模型拆解为横向误差模型,建立了横向控制模型。然后,采用极值法,建立融合了航向角误差和横向误差的积分滑模面,考虑一般指数趋近率难以消除的系统抖振问题,本文在改进指数趋近率的基础上引入了非线性激活函数,设计了一种基于激活函数滑模控制的横向路径跟踪控制器。最后,通过 Carsim-simulink 联合仿真对改进的滑模控制器进行双移线路况测试。结果表明,与传统的终端滑模控制器相比,优化后的积分滑模控制器的跟踪精度在低速低附着工况、高速高附着工况下的最大横向位置偏差分别提升了约64%、34.9%,平均横向位置偏差分别提升了约68.4%、59.7%,且优化后的控制器有效地抑制了车辆航向角、前轮转角的抖振超调变化,具有较强的鲁棒性。

    Abstract:

    The precision of path tracking is fundamental for the safe autonomous operation of intelligent vehicles. In order to address the vibration issue in sliding mode control systems and enhance the control precision of the path tracking controller, a novel Integral Sliding Mode Control strategy with Activation Function (PIDSM-AF) is proposed. Firstly, based on the two-degree-of-freedom vehicle model, the dynamic model of the vehicle is decomposed into a lateral error model to establish the lateral control model. Then, employing the extremum method, an integral sliding mode surface incorporating both heading angle error and lateral error is constructed. Considering the difficulty of eliminating system vibrations with general exponential convergence rates, this study introduces a nonlinear activation function based on the improved exponential convergence rate and designs a lateral path tracking controller based on the activation function sliding mode control. Finally, the improved sliding mode controller is subjected to double lane-change tests through Carsim-Simulink co-simulation. The results indicate that compared to the traditional terminal sliding mode controller, the tracking accuracy of the optimized integral sliding mode controller is improved by approximately 64% and 34.9% in maximum lateral position deviation under low-speed low-adhesion and high-speed high-adhesion conditions respectively, and the average lateral position deviation is improved by approximately 68.4% and 59.7%. Moreover, the optimized controller effectively suppresses the oscillations and overshoot variations of the vehicle"s heading angle and front wheel angle, demonstrating strong robustness.

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张 涌,张 闯,赵奉奎,李冰林,吕立亚.基于PIDSM-AF的智能车辆横向控制研究[J].南京信息工程大学学报,,():

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  • 收稿日期:2024-03-26
  • 最后修改日期:2024-05-21
  • 录用日期:2024-05-27

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