{"title":"Active Front Steering Controller Design with Side Slip Angle Free Model Matching Approach","authors":"Mert Sever, M. S. Arslan","doi":"10.1109/CEIT.2018.8751855","DOIUrl":null,"url":null,"abstract":"A side slip angle free model matching controller (MMC) is designed to improve vehicle yaw stability by active front steering. Optimization of controller gains is specified by a classical LQR problem. Additionally, LQR controller gains are structured to enable side slip angle free design. Design of an LQR having a structured controller gain is formulated as a convex optimization problem subject to linear matrix inequalities (LMIs) constraints. The proposed controller is designed with an augmented state space model including a linear bicycle model and model matching error dynamics. Superiority of the proposed controller is shown by numerically comparing with a classical full state feedback LQR. In order to obtain realistic results; a three-degrees-of-freedom nonlinear vehicle model is used. The nonlinear vehicle model is composed of lateral, yaw and longitudinal motions with the well-known Magic Formula tire model. Simulation results show that the proposed structured MMC provides very compatible performance with full state feedback LQR design.","PeriodicalId":357613,"journal":{"name":"2018 6th International Conference on Control Engineering & Information Technology (CEIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 6th International Conference on Control Engineering & Information Technology (CEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEIT.2018.8751855","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A side slip angle free model matching controller (MMC) is designed to improve vehicle yaw stability by active front steering. Optimization of controller gains is specified by a classical LQR problem. Additionally, LQR controller gains are structured to enable side slip angle free design. Design of an LQR having a structured controller gain is formulated as a convex optimization problem subject to linear matrix inequalities (LMIs) constraints. The proposed controller is designed with an augmented state space model including a linear bicycle model and model matching error dynamics. Superiority of the proposed controller is shown by numerically comparing with a classical full state feedback LQR. In order to obtain realistic results; a three-degrees-of-freedom nonlinear vehicle model is used. The nonlinear vehicle model is composed of lateral, yaw and longitudinal motions with the well-known Magic Formula tire model. Simulation results show that the proposed structured MMC provides very compatible performance with full state feedback LQR design.