{"title":"基于模型预测控制的四轮转向车辆路径跟踪新方法","authors":"Rongqi Gu, Tianhang Wang, Bo Zhang, Zhijun Li, Tianpeng Li, Guangyi Chen","doi":"10.1109/ICARM58088.2023.10218925","DOIUrl":null,"url":null,"abstract":"Path following is a crucial technique for ensuring the safe and efficient operation of automatic electric vehicles. Four-wheel steering (4WS) technology is known to enhance the accuracy and flexibility of such vehicles. In this paper, we propose a new constrained model predictive control (MPC) based method for path-following, specifically for 4WS vehicles. To simplify the 4WS vehicle kinematics model, we use the assumption of pure rolling and simplify it to a single-track model. We employ a high-precision linearization transformation to convert the nonlinear kinematics models to a linear control-state system. Subsequently, we design a new objective function based on the tracking error model, and formulate the control problem as an optimization problem. Finally, we convert the optimization problem into a quadratic programming (QP) form with constraints that are suitable for real-time applications. We demonstrate the effectiveness of our proposed control method through simulation experiments.","PeriodicalId":220013,"journal":{"name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel Path Following for a Four-Wheel Steering Vehicle Based on Model Predictive Control\",\"authors\":\"Rongqi Gu, Tianhang Wang, Bo Zhang, Zhijun Li, Tianpeng Li, Guangyi Chen\",\"doi\":\"10.1109/ICARM58088.2023.10218925\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Path following is a crucial technique for ensuring the safe and efficient operation of automatic electric vehicles. Four-wheel steering (4WS) technology is known to enhance the accuracy and flexibility of such vehicles. In this paper, we propose a new constrained model predictive control (MPC) based method for path-following, specifically for 4WS vehicles. To simplify the 4WS vehicle kinematics model, we use the assumption of pure rolling and simplify it to a single-track model. We employ a high-precision linearization transformation to convert the nonlinear kinematics models to a linear control-state system. Subsequently, we design a new objective function based on the tracking error model, and formulate the control problem as an optimization problem. Finally, we convert the optimization problem into a quadratic programming (QP) form with constraints that are suitable for real-time applications. We demonstrate the effectiveness of our proposed control method through simulation experiments.\",\"PeriodicalId\":220013,\"journal\":{\"name\":\"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICARM58088.2023.10218925\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARM58088.2023.10218925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Novel Path Following for a Four-Wheel Steering Vehicle Based on Model Predictive Control
Path following is a crucial technique for ensuring the safe and efficient operation of automatic electric vehicles. Four-wheel steering (4WS) technology is known to enhance the accuracy and flexibility of such vehicles. In this paper, we propose a new constrained model predictive control (MPC) based method for path-following, specifically for 4WS vehicles. To simplify the 4WS vehicle kinematics model, we use the assumption of pure rolling and simplify it to a single-track model. We employ a high-precision linearization transformation to convert the nonlinear kinematics models to a linear control-state system. Subsequently, we design a new objective function based on the tracking error model, and formulate the control problem as an optimization problem. Finally, we convert the optimization problem into a quadratic programming (QP) form with constraints that are suitable for real-time applications. We demonstrate the effectiveness of our proposed control method through simulation experiments.