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Exogenous Disturbance Estimation for Autonomous Navigation around Small Celestial Bodies
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-4383-7316
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-6415-6982
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-3557-6782
Autonomous Driving Lab in Scania Group, Sweden.
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2022 (English)In: 2022 IEEE 61st Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers Inc. , 2022, p. 3760-3766Conference paper, Published paper (Refereed)
Abstract [en]

In this article, we propose the implementation of a Nonlinear Moving Horizon Estimation (NMHE) framework to estimate exogenous disturbances acting on a spacecraft for autonomous navigation around Small Celestial Bodies (SCBs). The estimation framework is coupled with a Nonlinear Model Predictive Control (NMPC) to promote robust autonomous operations in Space. The NMHE based exogenous disturbance estimation formulates a finite horizon optimization problem, while incorporating the lumped disturbances as an additional augmented state vector. Next, the estimated disturbance is utilized by the NMPC controller in a feed-forward manner. Numerous closed-loop simulations have been conducted to assess the validity of the proposed estimation and disturbance rejection framework by considering: a) Inertial hovering around two different asteroid bodies namely 433 Eros and Ryugu and b) unavailability of two primary accurate asteroid characterization data, the asteroid rotation rate na and the gravitational parameter μ. The presented results are compared with an Extended Kalman Filter (EKF) and NMPC formulation to validate the efficacy of the proposed framework.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2022. p. 3760-3766
Series
Proceedings of the IEEE Conference on Decision & Control, ISSN 0743-1546, E-ISSN 2576-2370
Keywords [en]
Autonomous navigation, Exogenous Disturbance Estimation, Nonlinear Model Predictive Control, Nonlinear Moving Horizon Estimation
National Category
Control Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-95531DOI: 10.1109/CDC51059.2022.9993130ISI: 000948128103024Scopus ID: 2-s2.0-85147024846ISBN: 978-1-6654-6761-2 (electronic)OAI: oai:DiVA.org:ltu-95531DiVA, id: diva2:1735017
Conference
2022 IEEE 61st Conference on Decision and Control (CDC22), December 6-9, 2022, Cancun, Mexico
Available from: 2023-02-07 Created: 2023-02-07 Last updated: 2024-03-07Bibliographically approved

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Kottayam Viswanathan, VigneshPapadimitriou, AndreasBanerjee, AvijitNikolakopoulos, George

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