ADAPTIVE REMEDIATION OF THE SPACE DEBRIS ENVIRONMENT USING FEEDBACK CONTROL G. L. Somma, H.G. Lewis, C. Colombo
4th International Workshop on Space Debris Modelling and Remediation Paris, 06-08 June 2016
The Model – Model description – Object types and their interactions – Feedback controller for the space environment
The space debris problem •
Total number of debris is increasing
Look the problem from a wider prospective
Need to define mitigation strategies able to control the whole population
Credit: NASA, 2016
Research objectives Analyse debris control strategies
Define future mitigation measures
Investigate multiple adaptive control strategies
E.g. of research questions
Will it be more effective to act evenly in Low Earth Orbit or have different strategies in certain regions depending on the severity of the problem? Is it better and enough to focus on only one remediation measure (e.g. active debris removal) or use a synergy of multiple ones?
Create a space debris model with a feedback controller 4
Reality vs. Model and Controller
Observed population (telescopes and radars)
* Reality Model
* IADC = Inter-Agency Space Debris Coordination Committee UN = United Nations
Model description •
Deterministic sources-sink model [Wetherill, 1967] – Intrinsic collision probability [Wetherill, 1967] – Collision rate [Kessler and Cour-Palais, 1978] Simplified Model
Launch profile (Courtesy of ESA*)
Mean from 8-yr cycle
Collisions type (catastrophic/damaging)
Based on energy
Number of fragments: NASA Standard Break-up model [Johnson et al., 2001; Krisko, 2011]
A priori; fixed number
Drag: piecewise exponential atmospheric model [King-Hele, 1987; Vallado, 2013]
f(h, A, m)
a, e, A, M
Coupled non-linear first-order differential equations
* ESA = European Space Agency. ** ADR = Active Debris Removal
*** PMD = Post Mission Disposal
Object types and their interactions New launches
Integer PMD ADR Natural decay
Explosion fragments Collision fragments
Initial population: LEO* residing objects (Courtesy of ESA)
PMD with residual lifetime and level of compliance
Main assumptions: – Circular orbits – No solar cycle and no solar radiation pressure – No other perturbations
* LEO = Low Earth Orbit
Proportional feedback controller
u (t ) k P e(t ) k P ( NT (t ) NT* ) e(t ) NT (t ) N
Previous work: [White and Lewis, 2014]
k P 0 umax k P emax k P umax
e(t ) 0
0 e(t ) emax
e(t ) emax 8
Validation: Comparison to the IADC 2013 study DAMAGE
Intacts Existing fragments
New fragments Total
Credit: IADC, 2013
Preliminary results: Analysis with a proportional control law Optimistic scenario •
90% compliance with PMD 25-yr rule
PMD starts in 2013, but acts from 2046 (2013+8+25)
Starts in 2020
Max 25 removals per year
Synergy of PMD and ADR
Simplified model of space debris population – Multi-attitude, multi-species – Fast quantitative results
– Working Proportional controller on ADR
Model assumptions and limitations – Circular bands – No solar cycle, solar activity
Validation of the model against IADC 2013 study
Preliminary results show the potential synergy of PMD and ADR
Future work Model upgrades: – 7 object types – Area and Mass classes
– Semi-major axis, eccentricity and inclination discretisation
Extend the controller – From Proportional to PID controller – ADR and PMD (residual lifetime, compliance)
Sensitivity analysis: – discretisation values (number and value of height, mass and area bins), – other inputs (initial population, launch traffic) – model behaviour (number of explosions and collisions).
– New features to be included: solar cycle, solar radiation pressure, eccentricity bins.
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Thank you for your attention Merci de votre attention
Gian Luigi Somma [email protected]
Astronautics research group, Faculty of Engineering and the Environment, University of Southampton, United Kingdom
ESA Space Debris Office
Part of this research was funded by the Doctoral Training Partnership through the EPSRC Grant EP/M50662X/1