{"title":"Performance Evaluation of a Moving Horizon Estimator for Multi-Rate Sensor Fusion with Time-Delayed Measurements","authors":"Rodolphe Dubois, S. Bertrand, A. Eudes","doi":"10.1109/ICSTCC.2018.8540711","DOIUrl":null,"url":null,"abstract":"In this paper, the use of a Moving Horizon Estimator (MHE) is investigated to address a class of state estimation problems dealing with multi-rate sensor fusion in presence of time-delayed measurements. As it makes use of a batch of past measurement and state estimates, MHE is indeed a good candidate to deal with “missing” measurements. Nevertheless, since Moving Horizon Estimation relies on solving online an optimization problem to compute the state estimate, its computational load may be prohibitive for practical implementation to fast dynamical systems. Therefore this paper proposes a computationaly efficient implementation scheme for a variable structure linear MHE dealing with multi-rate time-delayed measurements, in the case where an analytical solution of the underlying optimization problem can be found. A simulation example is considered for performance comparison of the proposed MHE with respect to several state-of-the-art estimators, in terms of accuracy and computation time.","PeriodicalId":308427,"journal":{"name":"2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSTCC.2018.8540711","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
In this paper, the use of a Moving Horizon Estimator (MHE) is investigated to address a class of state estimation problems dealing with multi-rate sensor fusion in presence of time-delayed measurements. As it makes use of a batch of past measurement and state estimates, MHE is indeed a good candidate to deal with “missing” measurements. Nevertheless, since Moving Horizon Estimation relies on solving online an optimization problem to compute the state estimate, its computational load may be prohibitive for practical implementation to fast dynamical systems. Therefore this paper proposes a computationaly efficient implementation scheme for a variable structure linear MHE dealing with multi-rate time-delayed measurements, in the case where an analytical solution of the underlying optimization problem can be found. A simulation example is considered for performance comparison of the proposed MHE with respect to several state-of-the-art estimators, in terms of accuracy and computation time.