High-Fidelity Discrete-Time State-Dependent Riccati Equation Filters for Stochastic Nonlinear Systems with Gaussian/Non-Gaussian Noises

Insu Chang, Joseph Bentsman

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

Abstract

Two filtering techniques are proposed by using the discrete-time state-dependent Riccati equation (D-SDRE) methodology. Detailed derivation of the D-SDRE-based filter (D-SDREF) with the two-step procedure (measurement and update) is provided under the assumption of Gaussian noises. The input-to-state stability of the error signal between the measured and the estimated signals is proven under reasonable assumptions on system properties. For the non-Gaussian distributed noises, we propose a filter by combining the D-SDREF and the particle filter (PF), named the combined D-SDRE/PF. Algorithms of D-SDREF and combined D-SDRE/PF are provided. Performance of the latter techniques is compared with that of several other ones through the use of a challenging numerical example. Using the latter example, the reliability and the efficacy of the proposed D-SDREF and the combined D-SDRE/PF are demonstrated.

Original languageEnglish (US)
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1132-1137
Number of pages6
ISBN (Print)9781538654286
DOIs
StatePublished - Aug 9 2018
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Publication series

NameProceedings of the American Control Conference
Volume2018-June
ISSN (Print)0743-1619

Other

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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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