Xing-nan Zhou, Heran Shen, Zejiang Wang, Jun-ming Wang
{"title":"自调度L1鲁棒车辆侧滑角估计","authors":"Xing-nan Zhou, Heran Shen, Zejiang Wang, Jun-ming Wang","doi":"10.23919/ACC53348.2022.9867707","DOIUrl":null,"url":null,"abstract":"Respecting vehicle dynamics, the sideslip angle is a vitally important state for assessing and maintaining the lateral stability. As a practical barrier, the direct sensory measurement for such a state is overly expensive and not always reliable. In view of this, a self-scheduled L1 robust observer is synthesized in this paper to estimate the sideslip angle. Three objectives are achieved via the proposed estimation algorithm. First, the peak-to-peak induced gain from the exogenous disturbances to the estimation error is attenuated. Second, exploiting the Modified Finsler’s Lemma, the proposed strategy is effectually robust against bounded tire cornering stiffness perturbations. Third, the time-varying vehicular longitudinal velocity is compensated for by a polytopic gain-scheduling scheme. The proposed robust observer is corroborated via the high-fidelity CARSIM simulation, and its performance is contrasted against a baseline method.","PeriodicalId":366299,"journal":{"name":"2022 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Self-scheduled L1 Robust Vehicular Sideslip Angle Estimation\",\"authors\":\"Xing-nan Zhou, Heran Shen, Zejiang Wang, Jun-ming Wang\",\"doi\":\"10.23919/ACC53348.2022.9867707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Respecting vehicle dynamics, the sideslip angle is a vitally important state for assessing and maintaining the lateral stability. As a practical barrier, the direct sensory measurement for such a state is overly expensive and not always reliable. In view of this, a self-scheduled L1 robust observer is synthesized in this paper to estimate the sideslip angle. Three objectives are achieved via the proposed estimation algorithm. First, the peak-to-peak induced gain from the exogenous disturbances to the estimation error is attenuated. Second, exploiting the Modified Finsler’s Lemma, the proposed strategy is effectually robust against bounded tire cornering stiffness perturbations. Third, the time-varying vehicular longitudinal velocity is compensated for by a polytopic gain-scheduling scheme. The proposed robust observer is corroborated via the high-fidelity CARSIM simulation, and its performance is contrasted against a baseline method.\",\"PeriodicalId\":366299,\"journal\":{\"name\":\"2022 American Control Conference (ACC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 American Control Conference (ACC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ACC53348.2022.9867707\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ACC53348.2022.9867707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Respecting vehicle dynamics, the sideslip angle is a vitally important state for assessing and maintaining the lateral stability. As a practical barrier, the direct sensory measurement for such a state is overly expensive and not always reliable. In view of this, a self-scheduled L1 robust observer is synthesized in this paper to estimate the sideslip angle. Three objectives are achieved via the proposed estimation algorithm. First, the peak-to-peak induced gain from the exogenous disturbances to the estimation error is attenuated. Second, exploiting the Modified Finsler’s Lemma, the proposed strategy is effectually robust against bounded tire cornering stiffness perturbations. Third, the time-varying vehicular longitudinal velocity is compensated for by a polytopic gain-scheduling scheme. The proposed robust observer is corroborated via the high-fidelity CARSIM simulation, and its performance is contrasted against a baseline method.