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Adaptive remediation of the space debris environment using feedback control

Adaptive remediation of the space debris environment using feedback control
Adaptive remediation of the space debris environment using feedback control
This work presents a source-sink debris evolutionary model of the Low Earth Orbit (LEO) with a proportional control on Active Debris Removal (ADR). The model is based on a set of first order differential equations, which describe the injection and removal rates in several altitude bands within the LEO. Explosions and collisions generate fragments via the standard NASA breakup model, while Post Mission Disposal (PMD) and ADR are the removing mechanisms. Drag, the only natural sink mechanism, is computed through a piecewise exponential model of the atmospheric density, assuming that all objects have circular orbits. The model also includes a feedback controller on ADR where the number of removals is proportional to orbital population. The proposed control mimics the human-driven corrective actions arising from the review and adaptation of debris mitigation policies. The model is validated and then preliminary results are reported. They highlight that a synergy of PMD and ADR can reduce the number of removals needed for the current population to be maintained over a 200-year timeframe.
space debris, space debris modelling
Somma, Gian Luigi
fe2f9516-1fdb-4b9b-a4ce-7b6a7e60b49a
Lewis, Hugh
e9048cd8-c188-49cb-8e2a-45f6b316336a
Colombo, Camilla
595ced96-9494-40f2-9763-ad4a0f96bc86
Somma, Gian Luigi
fe2f9516-1fdb-4b9b-a4ce-7b6a7e60b49a
Lewis, Hugh
e9048cd8-c188-49cb-8e2a-45f6b316336a
Colombo, Camilla
595ced96-9494-40f2-9763-ad4a0f96bc86

Somma, Gian Luigi, Lewis, Hugh and Colombo, Camilla (2016) Adaptive remediation of the space debris environment using feedback control. 67th International Astronautical Congress (IAC), Guadalajara, Mexico. 26 - 30 Sep 2016. 11 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

This work presents a source-sink debris evolutionary model of the Low Earth Orbit (LEO) with a proportional control on Active Debris Removal (ADR). The model is based on a set of first order differential equations, which describe the injection and removal rates in several altitude bands within the LEO. Explosions and collisions generate fragments via the standard NASA breakup model, while Post Mission Disposal (PMD) and ADR are the removing mechanisms. Drag, the only natural sink mechanism, is computed through a piecewise exponential model of the atmospheric density, assuming that all objects have circular orbits. The model also includes a feedback controller on ADR where the number of removals is proportional to orbital population. The proposed control mimics the human-driven corrective actions arising from the review and adaptation of debris mitigation policies. The model is validated and then preliminary results are reported. They highlight that a synergy of PMD and ADR can reduce the number of removals needed for the current population to be maintained over a 200-year timeframe.

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More information

Accepted/In Press date: 8 September 2016
e-pub ahead of print date: 26 September 2016
Published date: 26 September 2016
Additional Information: Associated publication: Somma, G. L., Colombo, C., & Lewis, H. (2017). A statistical LEO model to investigate adaptable debris control strategies. In T. Flohrer, & F. Schmitz (Eds.), Proceedings 7th European Conference on Space Debris, Darmstadt, Germany, 18–21 April 2017,. European Space Agency (ESA).
Venue - Dates: 67th International Astronautical Congress (IAC), Guadalajara, Mexico, 2016-09-26 - 2016-09-30
Keywords: space debris, space debris modelling
Organisations: Astronautics Group

Identifiers

Local EPrints ID: 403265
URI: http://eprints.soton.ac.uk/id/eprint/403265
PURE UUID: 134db508-4a74-45e8-aac2-fc6094a750b7
ORCID for Hugh Lewis: ORCID iD orcid.org/0000-0002-3946-8757
ORCID for Camilla Colombo: ORCID iD orcid.org/0000-0001-9636-9360

Catalogue record

Date deposited: 29 Nov 2016 13:38
Last modified: 16 Mar 2024 02:55

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Contributors

Author: Gian Luigi Somma
Author: Hugh Lewis ORCID iD
Author: Camilla Colombo ORCID iD

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