{"title":"Nonlinear robust control of trajectory-following for autonomous ground electric vehicles with active front steering system","authors":"Xianjian Jin, Qikang Wang, Zeyuan Yan, Hang Yang","doi":"10.3934/math.2023565","DOIUrl":null,"url":null,"abstract":"This paper presents a nonlinear robust H-infinity control strategy for improving trajectory following performance of autonomous ground electric vehicles (AGEV) with active front steering system. Since vehicle trajectory dynamics inherently influenced by various driving maneuvers and road conditions, the main objective is to deal with the trajectory following control challenges of parametric uncertainties, system nonlinearities, and external disturbance. The AGEV system dynamics and its uncertain vehicle trajectory following system are first modeled and constructed, in which parameter uncertainties related to the physical limits of tire are considered and handled, then the control-oriented vehicle trajectory following augmented system with dynamic error is developed. The resulting nonlinear robust H-infinity state-feedback controller (NHC) of vehicle trajectory-following system is finally designed by H-infinity performance index and nonlinear compensation under AGEV system requirements, and solved utilizing a set of linear matrix inequalities derived from quadratic H-infinity performance and Lyapunov stability. Simulations for double lane change and serpentine scenes are carried out to verify the effectiveness of the proposed controller with a high-fidelity, CarSim®, full-vehicle model. It is found from the results that the proposed NHC provides improved vehicle trajectory following performance compared with the linear quadratic regulator (LQR) controller and robust H-infinity state-feedback controller (RHC).","PeriodicalId":48562,"journal":{"name":"AIMS Mathematics","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIMS Mathematics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.3934/math.2023565","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 11
Abstract
This paper presents a nonlinear robust H-infinity control strategy for improving trajectory following performance of autonomous ground electric vehicles (AGEV) with active front steering system. Since vehicle trajectory dynamics inherently influenced by various driving maneuvers and road conditions, the main objective is to deal with the trajectory following control challenges of parametric uncertainties, system nonlinearities, and external disturbance. The AGEV system dynamics and its uncertain vehicle trajectory following system are first modeled and constructed, in which parameter uncertainties related to the physical limits of tire are considered and handled, then the control-oriented vehicle trajectory following augmented system with dynamic error is developed. The resulting nonlinear robust H-infinity state-feedback controller (NHC) of vehicle trajectory-following system is finally designed by H-infinity performance index and nonlinear compensation under AGEV system requirements, and solved utilizing a set of linear matrix inequalities derived from quadratic H-infinity performance and Lyapunov stability. Simulations for double lane change and serpentine scenes are carried out to verify the effectiveness of the proposed controller with a high-fidelity, CarSim®, full-vehicle model. It is found from the results that the proposed NHC provides improved vehicle trajectory following performance compared with the linear quadratic regulator (LQR) controller and robust H-infinity state-feedback controller (RHC).
期刊介绍:
AIMS Mathematics is an international Open Access journal devoted to publishing peer-reviewed, high quality, original papers in all fields of mathematics. We publish the following article types: original research articles, reviews, editorials, letters, and conference reports.