Robust Hybrid Kalman Filter for a Class of Nonlinear Systems

Bharani P. Malladi, Ricardo G. Sanfelice, Eric Butcher

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

Abstract

Motivated by real-world applications with intermittent sensor data, an extended Kalman filter is formulated as a hybrid system and constructive conditions on its parameters guaranteeing an asymptotic stability property are provided. The dynamical properties of the estimation error are first characterized infinitesimally so to yield bounds on the rate of convergence and overshoot that depend on the parameters. By recasting the problem as the stabilization of a compact set, robustness properties of the proposed algorithm in the presence of disturbances in the system dynamics as well as measurement noise in the output are established. The proposed strategy is applied to spacecraft relative motion control with position-only measurements.

Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages628-633
Number of pages6
Volume2018-June
ISBN (Print)9781538654286
DOIs
Publication statusPublished - Aug 9 2018
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Other

Other2018 Annual American Control Conference, ACC 2018
CountryUnited States
CityMilwauke
Period6/27/186/29/18

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Malladi, B. P., Sanfelice, R. G., & Butcher, E. (2018). Robust Hybrid Kalman Filter for a Class of Nonlinear Systems. In 2018 Annual American Control Conference, ACC 2018 (Vol. 2018-June, pp. 628-633). [8431473] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2018.8431473