自动化学报2017，Vol.43Issue(11)：1931-1940,10.DOI:10.16383/j.aas.2017.c160633
基于无模型自适应控制的无人驾驶汽车横向控制方法
Model-free Adaptive Control Based Lateral Control of Self-driving Car
摘要
Abstract
In this paper, a control scheme based on model free adaptive control is proposed for the lateral control problem of self-driving car. First, the trajectory tracking problem for self-driving car is converted into the stabilization problem concerning a preview-deviation-yaw. Then, the lateral control system of the self-driving car is converted into a virtual dynamical linearization data model via a novel dynamic linearization technique. After that,a model free adaptive control algorithm, and its corresponding pseudo gradient estimating algorithm and pseudo gradient resetting algorithm are designed, such that the automatic drive of the self-driving car can be realized. The implementation of the proposed method only utilizes the input and output data of the self-driving car, avoiding complex modeling of the self-driving car. Thus,it has good adaptability to complex operation processes of self-driving car and is also applicable to other self-driving cars. Furthermore, the proposed scheme is employed in the experimental platform of self-driving car developed by Tsinghua University. Finally,the effectiveness of the proposed method is verified via the field tests in Fengtai District, Beijing, the field tests in the freeway of Changshu, Jiangsu, and the field applications in"2015 Chinese Intelligent Car Future Challenge Competition".关键词
无模型自适应控制/无人驾驶汽车/横向控制/预瞄偏差角Key words
Model-free adaptive control(MFAC)/self-driving car/lateral control/preview-deviation-yaw引用本文复制引用
田涛涛,侯忠生,刘世达,邓志东..基于无模型自适应控制的无人驾驶汽车横向控制方法[J].自动化学报,2017,43(11):1931-1940,10.基金项目
国家自然科学基金(61120106009, 61433002, 91420106),北京市自然科学基金–交控科技轨道交通联合基金(W17E000020) 资助 Supported by National Natural Science Foundation of China (61120106009, 61433002, 91420106), Beijing Natural Science Foundation Joint Fund for Science and Technology Rail Trans-portation (W17E000020) （61120106009, 61433002, 91420106）
