Attack-resilient Estimation for Linear Discrete-time Stochastic Systems with Input and State Constraints

Wenbin Wan, Hunmin Kim, Naira Hovakimyan, Petros G. Voulgaris

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, an attack-resilient estimation algorithm is developed for linear discrete-time stochastic systems with inequality constraints on the actuator attacks and states. The proposed algorithm consists of optimal estimation and information aggregation. The optimal estimation provides minimum-variance unbiased (MVU) estimates, and then they are projected onto the constrained space in the information aggregation step. It is shown that the estimation errors and their covariances from the proposed algorithm are less than those from the unconstrained algorithm. Moreover, we proved that the state estimation errors of the proposed estimation algorithm are practically exponentially stable. A simulation on mobile robots demonstrates the effectiveness of the proposed algorithm compared to an existing algorithm.

Original languageEnglish (US)
Title of host publication2019 IEEE 58th Conference on Decision and Control, CDC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5107-5112
Number of pages6
ISBN (Electronic)9781728113982
DOIs
StatePublished - Dec 2019
Event58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France
Duration: Dec 11 2019Dec 13 2019

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2019-December
ISSN (Print)0743-1546

Conference

Conference58th IEEE Conference on Decision and Control, CDC 2019
CountryFrance
CityNice
Period12/11/1912/13/19

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Fingerprint Dive into the research topics of 'Attack-resilient Estimation for Linear Discrete-time Stochastic Systems with Input and State Constraints'. Together they form a unique fingerprint.

  • Cite this

    Wan, W., Kim, H., Hovakimyan, N., & Voulgaris, P. G. (2019). Attack-resilient Estimation for Linear Discrete-time Stochastic Systems with Input and State Constraints. In 2019 IEEE 58th Conference on Decision and Control, CDC 2019 (pp. 5107-5112). [9029918] (Proceedings of the IEEE Conference on Decision and Control; Vol. 2019-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC40024.2019.9029918