{"title":"基于LPV观测器的车辆横向动力学故障传感器检测与估计","authors":"I. Alaridh, A. Aitouche, A. Zemouche","doi":"10.1109/ICOSC.2018.8587847","DOIUrl":null,"url":null,"abstract":"This paper deals with a fault sensor detection and estimation based on Unknown Input Observer (UIO) for vehicle lateral dynamics. The vehicle lateral dynamics is represented by a fourth degree of freedom model. This nonlinear model is transformed into linear parameter varying model where the longitudinal velocity is considered as parameter varying. Then, an Unknown Input Observer is designed in order to reconstruct the state variables in presence of sensor faults.Based on Lyapunov theory, the observer gains are computed by Linear Matrix Inequalities. The approach can discriminate sensor faults from disturbances. Simulation results are given to show the effectiveness of the proposed approach to detect sensor faults subject to disturbances.","PeriodicalId":153985,"journal":{"name":"2018 7th International Conference on Systems and Control (ICSC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fault Sensor Detection and Estimation based on LPV Observer for Vehicle Lateral Dynamics\",\"authors\":\"I. Alaridh, A. Aitouche, A. Zemouche\",\"doi\":\"10.1109/ICOSC.2018.8587847\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with a fault sensor detection and estimation based on Unknown Input Observer (UIO) for vehicle lateral dynamics. The vehicle lateral dynamics is represented by a fourth degree of freedom model. This nonlinear model is transformed into linear parameter varying model where the longitudinal velocity is considered as parameter varying. Then, an Unknown Input Observer is designed in order to reconstruct the state variables in presence of sensor faults.Based on Lyapunov theory, the observer gains are computed by Linear Matrix Inequalities. The approach can discriminate sensor faults from disturbances. Simulation results are given to show the effectiveness of the proposed approach to detect sensor faults subject to disturbances.\",\"PeriodicalId\":153985,\"journal\":{\"name\":\"2018 7th International Conference on Systems and Control (ICSC)\",\"volume\":\"80 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 7th International Conference on Systems and Control (ICSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSC.2018.8587847\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 7th International Conference on Systems and Control (ICSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSC.2018.8587847","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fault Sensor Detection and Estimation based on LPV Observer for Vehicle Lateral Dynamics
This paper deals with a fault sensor detection and estimation based on Unknown Input Observer (UIO) for vehicle lateral dynamics. The vehicle lateral dynamics is represented by a fourth degree of freedom model. This nonlinear model is transformed into linear parameter varying model where the longitudinal velocity is considered as parameter varying. Then, an Unknown Input Observer is designed in order to reconstruct the state variables in presence of sensor faults.Based on Lyapunov theory, the observer gains are computed by Linear Matrix Inequalities. The approach can discriminate sensor faults from disturbances. Simulation results are given to show the effectiveness of the proposed approach to detect sensor faults subject to disturbances.