摘要
针对智能车辆视觉导航横向控制中存在的适应性问题,提出了一种基于横摆角速度与横向偏差的智能车辆横向模糊控制策略。根据车辆于车道内的位置状态信息,建立了横摆角速度预测模型、7自由度车辆操纵动力学模型以及横向模糊推理模型。仿真结果表明,与常规位置偏差控制策略相比较,采用横向模糊控制策略不仅能提高智能车辆横向控制的精确性,并且具有很好的鲁棒性和自适应性。
According to the intelligent vehicle visual navigation lateral control of the adaptability of the existing problems, a lateral fuzzy control strategy based on yaw rate is proposed. According to the position of the vehicle in the lane state information, a yaw-rate prediction model, 7 degrees of freedom vehicle handling dynamics model and lateral fuzzy control model are established. Simulation result shows that compared with conventional position deviation control strategy, the lateral fuzzy control strategy can not only effectively control intelligent vehicle to run, but also have good robustness and adaptability.
出处
《电子技术应用》
北大核心
2014年第9期130-132,136,共4页
Application of Electronic Technique
关键词
智能车辆
横向控制
模糊控制
仿真研究
intelligent vehicle
lateral control
fuzzy control
simulation research
