{"title":"Two-stage Kalman filter for simultaneous fault and delay estimation in networked control systems","authors":"K. Chabir, D. Sauter, I. Al-Salami, M. Abdelkrim","doi":"10.1109/MED.2010.5547676","DOIUrl":null,"url":null,"abstract":"Networked Control Systems are becoming very popular nowadays. However, the use of networks in the control loop induces extra difficulties in diagnosis. In this paper we propose a method for estimate fault as well delay induced by the network. Inspired from the Kalman filter previously proposed by Sinopoli et al. and Hsieh et al., two solutions are presented; the augmented and the two-stage Kalman filter. Main attention is paid for the last one. The delay and the fault are integrated as a state variable. It is supposed that the delay and the fault are random variables. In addition, we provide some analytic results to demonstrate the computational advantages of two-stage Kalman filter over augmented ones. An example illustrates the obtained results is given.","PeriodicalId":149864,"journal":{"name":"18th Mediterranean Conference on Control and Automation, MED'10","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th Mediterranean Conference on Control and Automation, MED'10","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MED.2010.5547676","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Networked Control Systems are becoming very popular nowadays. However, the use of networks in the control loop induces extra difficulties in diagnosis. In this paper we propose a method for estimate fault as well delay induced by the network. Inspired from the Kalman filter previously proposed by Sinopoli et al. and Hsieh et al., two solutions are presented; the augmented and the two-stage Kalman filter. Main attention is paid for the last one. The delay and the fault are integrated as a state variable. It is supposed that the delay and the fault are random variables. In addition, we provide some analytic results to demonstrate the computational advantages of two-stage Kalman filter over augmented ones. An example illustrates the obtained results is given.