文献类型：会议论文

英文题名：Research on Control Method of Self-driving Vehicle Based on Adaptive Fuzzy PID

作者：Yao, Yongqiang[1]; Ma, Nan[2]; Li, Jiahong[3]; Wu, Zhixuan[1]; Zhang, Guoping[1]

第一作者：Yao, Yongqiang

机构：[1] Beijing Union University, Beijing Key Laboratory of Information Service Engineering, Beijing, 100101, China; [2] Beijing University of Technology, Faculty of Information Technology, Beijing, 100124, China; [3] College of Robotics, Beijing Union University, Beijing, 100101, China

第一机构：北京联合大学北京市信息服务工程重点实验室

会议论文集：Proceedings - 2021 17th International Conference on Computational Intelligence and Security, CIS 2021

会议日期：November 19, 2021 - November 22, 2021

会议地点：Chengdu, China

语种：英文

外文关键词：Automobile drivers - Control system synthesis - Controllers - Electric control equipment - Fuzzy inference - Fuzzy rules - Proportional control systems - Vehicles

摘要：In the control of self-driving vehicles, PID controllers are widely used, because of their simple structure and good stability. However, in a complex self-driving environment, different scenarios have different requirements for vehicle control accuracy. At this time, using a set of PID parameters may not meet the requirements. In order to solve this problem, we proposed an adaptive fuzzy PID controller. Specifically, firstly, we added a rule partition table on the basis of fuzzy PID. Secondly, vehicle sensors recognize the scene. Thirdly, the fuzzy rules are determined by the rule partition table, and the PID parameters are adjusted in different scenarios in real time. Finally, we Use this method to test in Panosim simulation environment, the control accuracy is better than PID control in right-angle corners, overtaking and other scenes. ? 2021 IEEE.