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基于模糊神经网络的车辆间距智能自适应控制

Intelligent adaptive control of the longitudinal distances between running vehicles by neural networks

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【作者】 余晓江胡学军胡于进王学林

【Author】 Yu Xiaojiang1 Hu Xuejun2 Hu Yujin2 Wang Xuelin2,3(1 School of Mechanical and Vehicular Engineering,Beijing Institute of Technology,Beijing 100081,China;2 College of Mechanical Science and Engineering,Huazhong University ofScience and Technology,Wuhan 430074,China; 3 State Key Lab of Vehicle Transmission,Northern Vehicle Institute,Beijing 100072,China)

【机构】 北京理工大学机械与车辆工程学院华中科技大学机械科学与工程学院华中科技大学机械科学与工程学院 北京100081湖北武汉430074北方车辆研究所车辆传动国家重点实验室北京100072

【摘要】 为了实现汽车行驶过程中与前车车距的自动控制,提出了一种基于模糊神经网络的车辆纵向间距智能自适应控制方法.利用神经网络对车辆纵向运动进行辨识,将神经网络和模糊控制结合起来,设计模糊神经网络加速度控制器,利用神经网络的学习功能修正控制器的隶属度函数的参数和控制规则.仿真表明系统响应快,控制精度高,和传统方法相比具有较强的抗干扰能力和自适应性.

【Abstract】 Combined fuzzy control with neural network,based on the control model for the longitudinal relative distances between running vehicle and vehicle,a fuzzy neural network acceleration controller was designed.An identification model for the vehicle longitudinal movement was built through neural network.By using the learning function of the neural network,the membership functions and the inference rules in the controller were modified so that the adaptability of the controller is further enhanced.Simulation results show the system is robust and capable of anti-interference.

【基金】 科技部基础研究资助项目(K0304050201)
  • 【文献出处】 华中科技大学学报(自然科学版) ,Journal of Huazhong University of Science and Technology(Nature Science Edition) , 编辑部邮箱 ,2007年09期
  • 【分类号】TP273.2;TP183
  • 【被引频次】24
  • 【下载频次】385
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