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.
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.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2007年第9期22-24,共3页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
科技部基础研究资助项目(K0304050201)
关键词
汽车纵向动力学
车距控制
模糊神经网络
自适应控制
vehicles longitudinal dynamic
spacing control
fuzzy neural network
adaptive control
