AUTONOMOUS CONTROL SYSTEM FOR SATELLITE FORMATION FLYING

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AUTONOMOUS CONTROL SYSTEM FOR SATELLITE FORMATION
FLYING

• K Thanapalan and S M Veres
• School of Engineering Sciences,
• The University of Southampton

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Outline of the presentation

• Formation Flying Concept
• Activity at Southampton
• The analytic (control) problems
• The multiple agent architecture
• Commands and messages
• Conclusions on verification
• Illustration

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Formation Flying Concept

• Idea Replace a large and unpractical satellite
  by several small and less expensive ones.
• Advantages
• Emulated system more flexible.
• Failure of a satellite gt deterioration of the
  system, system performance, but does not
  jeopardise the whole mission.

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• Formation Flying Concept

concept pursued NASA and ESA and some other
agencies.
TS3links separate telescopes together to produce
one large image.
(NASA pictures)
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• Formation Flying Projects at the School of
  Engineering Sciences
• University of Southampton

• Constrained controller design project (optimal
  design software, EPSRC 178k)
• Formation Flying electronics testing facility (5
  DOF frames into which control systems can be
  plugged into for testing, EPSRC 80k
• Partners EADS Astrium and Aero-Astro

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Laboratory Hardware 3 mockup satellites of 5DOF
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• Formation Flying challenges

Virtual forces acting on a follower craft
around a leader on natural orbit at 0,0,0
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• Formation Flying control challenges

• Thruster resolution quantized forces and
  limited forces on electrical thrusters (lt10mN)
• Thrusters generate torques not only
  translational forces. Possibly varying mass
  centre requires adaptation of controls to keep
  prescribed attitude while translation is
  performed by thrusters.
• Constraints on thruster forces make some
  formations impossible

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• Formation Flying challenges

• Collision avoidance while switching to new
  formation
• Sensor deterioration or failures (gyros,
  horizon, sun, star sensors and stereo-vision
  system)
• Actuator deterioration or failures (electric
  propulsion, reaction wheel, control moment gyro
  problems)
• Autonomous control (there is no time for ground
  control to calculate necessary action before a
  satellite can fatally drift off from the cluster

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• Formation Flying do we need agent technology ?

• Probably it could be done in object oriented
  programming, but ...
• Each satellite needs to communicate with the
  others,
• Each satellite has to make decisions on the
  basis of sensed and received information and
  commands.
• Each satellite must be self-reliant in case of
  joint operation emergency caused by faults in the
  system. For instance must keep itself close to
  the cluster even if it cannot communicate with
  their peers.
• Conclusion object oriented programming appears
  to be more tedious to deploy then agent oriented
  programming

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What agent functionality is needed?

• Cluster level agents to serve the cluster as a
  whole (not just an individual satellite) a
  mission manager, a cluster path planner and data
  fusion agents to combine all measurements to
  improve accuracy
• Multi-agents on board each craft a control
  devices handler, a sensor handler and a local
  manager
• Commands and data communication between mission
  manager and local managers
• Commands and data communication between mission
  manager and local managers

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The analytic control problems

• Adaptive tracking of position and attitude
  various globally stable Lyapunov design based,
  adaptive control methods have been developed
  during the last few years
• Fuel efficient path planning under no
  constraints (solutions derived by the Pontryagin
  principle.)
• Input constrained solutions to fuel efficient
  formation control used for path planning.
• Extended Kalman filtering for stereo vision
  based attitude and position estimation of each
  craft based on measurements taken by all
  instruments of the cluster of satellites in the
  formation.

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Multi agent architecture for the cluster
For the whole cluster
Mission manager ...
Mission control (human)
Cluster path planner
Cluster data fusion
Maneuver Executor adaptive feedback controller
agent
Local manager
Controls handler
Local path planner agent
Sensors handler
Repeated on each satellite
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Commands received by the mission manager
Possible Commands to mission manager
- install and wake all agents data agent team
data
- send devices health report data
managers list
- send general
report data agent team data
-
send general log data depth of detail

- consider and report on a proposed formation
data formation object, formation info
- supervise a new formation
data formation object, team data
- predict power sources
to maintain current formation
- maintain current
formation
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Messages received by the mission manager
- From cluster planner checked conditions of
feasibility of proposed new formation - From
manager Sx started transfer to new formation
- From manager Sx finished transfer
to new formation, maintaining formation
- From manager Sx sensor Sx fault actuator
Ax fault - From manager
Sx software fault
messages
Install an agent, wake agents, send formation
commands make decision on reconfiguration,
organize emergency send report to mission
control, ask managers for physical health, ask
cluster planner, etc.
action set
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Multi agent architecture for the cluster
For the whole cluster
Mission manager ...
Mission control (human)
Cluster planner
Cluster data fusion
Maneuver Executor adaptive feedback controller
agent
Local manager
Controls handler
Local path planner agent
Sensors handler
Repeated on each satellite
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Messages received by the local manager

• - maintain formation
• - check devices
  
• - send health report
  
• - check conditions for new formation
• transfer to position in new formation

Commands from Mission manager

• received new path plan
• executing transfer
• unusual response of craft
• adaptation-log of operations

Messages from Controller
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Action set of local manager
Send message started transfer to new formation
Send message finished transfer to new
formation Send message sensor Sx fault
actuator Ax fault Monitor position Switch
controller scheme Send hardware health
report Send events log for last x minutes Predict
position of other satellites Ask for modified
path Compute emergence path Change path to
track
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Multi agent architecture for the cluster
For the whole cluster
Mission manager ...
Mission control (human)
Cluster planner
Cluster data fusion
Maneuver Executor adaptive feedback controller
agent
Local manager
Controls handler
Local path planner agent
Sensors handler
Repeated on each satellite
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Action set of cluster planner

• new formation request
• abort current planning process
• limited capabilities description
• send message working on transfer plan
• send transfer_plan_complete
• send requested transfer is not feasible

Incoming messages from mission manager
Outgoing messages
- computing new plan - idle
Action set
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Multi agent architecture for the cluster
For the whole cluster
Mission manager ...
Mission control (human)
Cluster planner
Cluster data fusion
Maneuver Executor adaptive feedback controller
agent
Local manager
Controls handler
Local path planner agent
Sensors handler
Repeated on each satellite
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Multi agent architecture for the cluster

• track path x
• use controller type x
• current positions are x
• current positions are x

commands from local manager
Outgoing messages

• Control going all right
• unusual craft response

Action set

• operate controller x to track p
• idle

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Multi agent architecture for the cluster
For the whole cluster
Mission manager ...
Mission control (human)
Cluster planner
Cluster data fusion
Maneuver Executor adaptive feedback controller
agent
Local manager
Controls handler
Local path planner agent
Sensors handler
Repeated on each satellite
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Sensor Data Fusion (SDF) agent

• It is essentially an enhanced estimator for the
  satellite position and attitude in the local
  coordinate system that also has the ability to
  report sensor problems
• It uses measurements obtained from sensors, if
  some data does not arrive or is faulty it is
  still able to come up with an estimate
• For each sensor there is a handler agent that is
  capable to monitor the reliability of the sensor
  (solid state gyros, stereo vision, star, Earth
  and Sun sensors) and reports malfunction to SDF

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Sensor Data Fusion (SDF) agent
Incoming messages
receive all gyro data receive all sun sensor
data receive all star data receive all vision
data receive all horizon data Receive all GPS
data
Action set
Estimate all positions and attitudes Broadcast
all positions and attitudes Report detected
malfunction
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Stereo vision system
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Joint control of attitude and position
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Further details of joint attitude and position
control of a single satellite

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Cluster level control

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A simple jet actuator configuration
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Progress so far

• We are still working on increasing messaging
  vocabulary
• We have coded the adaptive feedback control
  agents
• We are testing the SDF agent partly on real and
  partly on simulated data.
• The position and attitude data communicator
  essentially complete
• We have built a laboratory testing hardware
  including 3 satellite models.

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• Our conclusions and experience
• In our EPSRC projects it was not a requirement
  that we have to use agent technology but we have
  found them a useful technique that speeds up
  developing a reliable control structure.
• Verification We are using a minimal complexity
  agent architecture that does the job it can be
  modelled by a finite state machine if abstract
  the behaviour of the 4 analytic modules (1)
  path planning, (2) adaptive controller (3) data
  fusion filter
• If we assume that the analytic modules behave
  as predicted by physical laws and the floating
  point arithmetic based algorithms are 100
  reliable then the system is verifiable for a
  given set of failure modes.
• Agents are useful for functional modularity,
  reliability and maintainability of software.
  Encapsulation of behaviour allows easier testing
  and checking logical consistency of the whole
  system, i.e. verification.

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Thank you