{"title":"Energy dissipation based successive approximation algorithm for intelligent vehicle speed adaption*","authors":"Rui Zhang, Yulin Ma, Xiaofeng Liu","doi":"10.1109/FISTS.2016.7552319","DOIUrl":null,"url":null,"abstract":"This paper proposes a successive approximation algorithm (SAA) for intelligent vehicle speed adaption (IVSA) based on energy dissipation. As vehicle dynamical system resembles a series of mass/spring/damper systems that are dissipative, i.e., the energy of the system decays to zero eventually, the problem of IVSA is transformed into dissipative control design based on energy storage function. In order to satisfy the γ-performance with respect to the quadratic supply rate, the storage function is developed by using a backstepping based Lyapunov method based on a step-by-step improvement of performance bounds. A dissipative control law is designed by a SAA with a step-by-step reduction of the value of γ. The IVSA simulations are given under variable acceleration condition, whose performances are verified by the comparison of both longitudinal and lateral tracking errors and energy-consuming in different values of γ.","PeriodicalId":179987,"journal":{"name":"2016 IEEE Forum on Integrated and Sustainable Transportation Systems (FISTS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Forum on Integrated and Sustainable Transportation Systems (FISTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FISTS.2016.7552319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a successive approximation algorithm (SAA) for intelligent vehicle speed adaption (IVSA) based on energy dissipation. As vehicle dynamical system resembles a series of mass/spring/damper systems that are dissipative, i.e., the energy of the system decays to zero eventually, the problem of IVSA is transformed into dissipative control design based on energy storage function. In order to satisfy the γ-performance with respect to the quadratic supply rate, the storage function is developed by using a backstepping based Lyapunov method based on a step-by-step improvement of performance bounds. A dissipative control law is designed by a SAA with a step-by-step reduction of the value of γ. The IVSA simulations are given under variable acceleration condition, whose performances are verified by the comparison of both longitudinal and lateral tracking errors and energy-consuming in different values of γ.