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Online Parameter Estimation of the B-Matrix of a Quadcopter in Time- and Frequency-Domain

  • Technical University of Munich

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The performance of control algorithms for eVTOL, like incremental nonlinear dynamic inversion (INDI), relies on precise models of the system. Instead of using pre-identified models, we aim to identify the model online. In this paper we compare sequential least squares in frequency-domain to extended Kalman filtering for identification of the B-matrix, used in INDI. We demonstrated the online identification of the B-matrix in mini-quadcopter flight tests. Both methods can identify constant and time-varying parameters, but only with sufficient excitation. Otherwise, the parameters cannot be estimated precisely and drift away. In this study, we lay the basis for integrating online parameter estimation into INDI.

Original languageEnglish
Title of host publicationAdvances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control
EditorsLiang Yan, Haibin Duan, Yimin Deng, Liang Yan
PublisherSpringer Science and Business Media Deutschland GmbH
Pages2758-2769
Number of pages12
ISBN (Print)9789811966125
DOIs
StatePublished - 2023
EventInternational Conference on Guidance, Navigation and Control, ICGNC 2022 - Harbin, China
Duration: 5 Aug 20227 Aug 2022

Publication series

NameLecture Notes in Electrical Engineering
Volume845 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Guidance, Navigation and Control, ICGNC 2022
Country/TerritoryChina
CityHarbin
Period5/08/227/08/22

Keywords

  • Extended Kalman filter
  • Online parameter estimation
  • Sequential least squares
  • System identification

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