Zixuan Qian, Zhuoping Yu, L. Xiong, Zhiqiang Fu, Dequan Zeng
{"title":"自动驾驶车辆路径跟踪的条件积分自抗扰控制器","authors":"Zixuan Qian, Zhuoping Yu, L. Xiong, Zhiqiang Fu, Dequan Zeng","doi":"10.1109/CVCI51460.2020.9338668","DOIUrl":null,"url":null,"abstract":"Aim at rejecting uncertainty disturbance and actuator saturation, a path tracking method is proposed for autonomous driving vehicles, which is implement by active disturbance rejection controller (ADRC) with conditional integration. Firstly, a kinematic-dynamic vehicle model is deduced for describing path tracking process. Secondly, a nonlinear extended state observer is designed to observe the uncertainty disturbance, such as external disturbance and parameter uncertainties. Finally, in order to eliminate error and reject disturbance while resisting actuator saturation, a conditional integration is developed as feedback control low. The test results of lane changing scenarios show that the proposed algorithm can track the desired path quickly and accurately compared with PID and ADRC.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Conditional Integration Active Disturbance Rejection Controller for Path Tracking of Autonomous Driving Vehicles\",\"authors\":\"Zixuan Qian, Zhuoping Yu, L. Xiong, Zhiqiang Fu, Dequan Zeng\",\"doi\":\"10.1109/CVCI51460.2020.9338668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aim at rejecting uncertainty disturbance and actuator saturation, a path tracking method is proposed for autonomous driving vehicles, which is implement by active disturbance rejection controller (ADRC) with conditional integration. Firstly, a kinematic-dynamic vehicle model is deduced for describing path tracking process. Secondly, a nonlinear extended state observer is designed to observe the uncertainty disturbance, such as external disturbance and parameter uncertainties. Finally, in order to eliminate error and reject disturbance while resisting actuator saturation, a conditional integration is developed as feedback control low. The test results of lane changing scenarios show that the proposed algorithm can track the desired path quickly and accurately compared with PID and ADRC.\",\"PeriodicalId\":119721,\"journal\":{\"name\":\"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVCI51460.2020.9338668\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVCI51460.2020.9338668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Conditional Integration Active Disturbance Rejection Controller for Path Tracking of Autonomous Driving Vehicles
Aim at rejecting uncertainty disturbance and actuator saturation, a path tracking method is proposed for autonomous driving vehicles, which is implement by active disturbance rejection controller (ADRC) with conditional integration. Firstly, a kinematic-dynamic vehicle model is deduced for describing path tracking process. Secondly, a nonlinear extended state observer is designed to observe the uncertainty disturbance, such as external disturbance and parameter uncertainties. Finally, in order to eliminate error and reject disturbance while resisting actuator saturation, a conditional integration is developed as feedback control low. The test results of lane changing scenarios show that the proposed algorithm can track the desired path quickly and accurately compared with PID and ADRC.