汽车工程

汽车工程 ›› 2019, Vol. 41 ›› Issue (8): 953-959.doi: 10.19562/j.chinasae.qcgc.2019.08.014

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基于模糊神经网络的智能汽车轨迹跟踪研究*

张炳力, 李子龙, 沈干, 方涛, 曹聪聪, 郑平平   

  1. 合肥工业大学汽车与交通工程学院,合肥 230009
  • 收稿日期:2018-07-11 出版日期:2019-08-25 发布日期:2019-09-03
  • 通讯作者: 李子龙,硕士,E-mail:641888403@qq.com
  • 基金资助:
    安徽省科技重大专项项目(JZ2015AKKZ0590)、国家重点研发计划项目(2017YFB0102503)和安徽省工程实验室

A Research on Path Tracking of Intelligent Vehicle Based on Fuzzy Neural Network

Zhang Bingli, Li Zilong, Shen Gan, Fang Tao, Cao Congcong, Zheng Pingping   

  1. School of Vehicle and Traffic Engineering,Hefei University of Technology, Hefei 230009
  • Received:2018-07-11 Online:2019-08-25 Published:2019-09-03

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摘要： 在研究传统动力学模型和预瞄模型的基础上,基于神经网络和模糊控制的理论,设计了一种轨迹跟踪控制器。利用神经网络的自学习和自调整特性,并结合模糊控制,分别设计神经网络对自车车速进行预测,并将其输出和侧向偏差等参数作为模糊神经网络的输入,控制转向盘转角。最后基于CarSim和Matlab/Simulink软件进行联合仿真,并进行实车试验,验证了所设计控制器的有效性和精确性。

关键词: 智能汽车, 轨迹跟踪, 神经网络, 模糊控制

Abstract: Based on the research of the traditional dynamics model and preview model, a kind of path tracking controller is designed in view of the theory of neural network and fuzzy control. Utilizing the self-learning and self-adjusting characteristics of neural network, combined with the advantages of fuzzy control, a kind of network is designed to predict the speed of vehicle and its output and lateral deviation are taken as the input of the fuzzy network to control the steering angle. Finally, the joint simulation by CarSim and Matlab/Simulink software is carried out and the actual vehicle experiment is done, having verified the effectiveness and accuracy of the designed controller

Key words: intelligent vehicle, path tracking, neural network, fuzzy control