Controller and Trajectory Optimization for a Quadrotor UAV with Parametric Uncertainty

Ali Srour, Antonio Franchi, Paolo Robuffo Giordano

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

7 Citations (Scopus)
148 Downloads (Pure)

Abstract

In this work, we exploit the recent notion of closed-loop state sensitivity to critically compare three typical controllers for a quadrotor UAV with the goal of evaluating the impact of controller choice, gain tuning and shape of the reference trajectory in minimizing the sensitivity of the closed-loop system against uncertainties in the model parameters. To this end, we propose a novel optimization problem that takes into account both the shape of the reference trajectory and the controller gains. We then run a large statistical campaign for comparing the performance of the three controllers which provides some interesting insight for the goal of increasing closed-loop robustness against parametric uncertainties.

Original languageEnglish
Title of host publication2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
PublisherIEEE
Pages9999-10005
Number of pages7
ISBN (Electronic)9781665491907
DOIs
Publication statusPublished - 13 Dec 2023
EventIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023 - Huntington Place, Detroit, United States
Duration: 1 Oct 20235 Oct 2023
https://ieee-iros.org/

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
Abbreviated titleIROS 2023
Country/TerritoryUnited States
CityDetroit
Period1/10/235/10/23
Internet address

Keywords

  • 2024 OA procedure

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