Robust moving horizon state estimation for uncertain linear systems using linear matrix inequalities
Author(s)
Georgiou, Anastasis
Tahir, Furqan
Evangelou, Simos
Jaimoukha, Imad
Type
Conference Paper
Abstract
This paper investigates the problem of state estimation for linear-time-invariant (LTI) discrete-time systems subject to structured feedback uncertainty and bounded disturbances. The proposed Robust Moving Horizon Estimation (RMHE) scheme computes at each sample time tight bounds on the uncertain states by solving a linear matrix inequality (LMI) optimization problem based on the available noisy input and output data. In comparison with conventional approaches that use offline calculation for the estimation, the suggested scheme achieves an acceptable level of performance with reduced conservativeness, while the online computational time is maintained relatively low. The effectiveness of the proposed estimation method is assessed via a numerical example.
Date Issued
2021-01-11
Date Acceptance
2020-07-15
Citation
2020 59th IEEE Conference on Decision and Control (CDC), 2021, pp.2900-2905
Publisher
IEEE
Start Page
2900
End Page
2905
Journal / Book Title
2020 59th IEEE Conference on Decision and Control (CDC)
Copyright Statement
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
59th IEEE Conference on Decision and Control - CDC 2020
Publication Status
Published
Start Date
2020-12-14
Finish Date
2020-12-18
Coverage Spatial
Jeju Island, Republic of Korea (Virtual)
Date Publish Online
2021-01-11