Softwalls: Preventing Aircraft from Entering Unauthorized Airspace

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Softwalls Preventing Aircraft from Entering
Unauthorized Airspace

• Adam Cataldo
• Prof. Edward Lee
• Ian Mitchell
• Prof. Shankar Sastry

CHESS Review May 8, 2003 Oakland, CA
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Outline

• Introduction to Softwalls
• Objections
• Control system progress
• Future challenges
• Conclusions

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IntroductionAvionics Application

• On-board database with no-fly-zones
• Enforce no-fly zones using on-board avionics
• Non-networked, non-hackable

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Autonomous control
Pilot
Aircraft
Autonomous controller
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Softwalls is not autonomous control
Pilot
Aircraft

bias pilot control
Softwalls
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Relation to Unmanned Aircraft

• Not an unmanned strategy
• pilot authority
• Collision avoidance

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A deadly weapon?

• Project started September 11, 2001

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Design Objectives
Maximize Pilot Authority!
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Unsaturated Control
Pilot lets off controls
Pilot tries to fly into no-fly zone
Pilot turns away from no-fly zone
No-fly zone
Control applied
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Objections

• Reducing pilot control is dangerous
• reduces ability to respond to emergencies

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There is No Emergency That Justifies Landing Here
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Objections

• Reducing pilot control is dangerous
• reduces ability to respond to emergencies
• There is no override
• switch in the cockpit

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Hardwall
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Objections

• Reducing pilot control is dangerous
• reduces ability to respond to emergencies
• There is no override
• switch in the cockpit
• Localization technology could fail
• GPS can be jammed

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Localization Backup

• Inertial navigation
• Integrator drift limits accuracy range

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Objections

• Reducing pilot control is dangerous
• reduces ability to respond to emergencies
• There is no override
• switch in the cockpit
• Localization technology could fail
• GPS can be jammed
• Deployment could be costly
• Software certification? Retrofit older aircraft?

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Deployment

• Fly-by-wire aircraft
• a software change
• Older aircraft
• autopilot level
• Phase in
• prioritize airports

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Objections

• Reducing pilot control is dangerous
• reduces ability to respond to emergencies
• There is no override
• switch in the cockpit
• Localization technology could fail
• GPS can be jammed
• Deployment could be costly
• how to retrofit older aircraft?
• Complexity
• software certification

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Not Like Air Traffic Control

• Much Simpler
• No need for air traffic controller certification

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Objections

• Reducing pilot control is dangerous
• reduces ability to respond to emergencies
• There is no override
• switch in the cockpit
• Localization technology could fail
• GPS can be jammed
• Deployment could be costly
• how to retrofit older aircraft?
• Deployment could take too long
• software certification
• Fully automatic flight control is possible
• throw a switch on the ground, take over plane

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Potential Problems with Ground Control

• Human-in-the-loop delay on the ground
• authorization for takeover
• delay recognizing the threat
• Security problem on the ground
• hijacking from the ground?
• takeover of entire fleet at once?
• coup detat?
• Requires radio communication
• hackable
• jammable

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Heres How It Works
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Reachable Set
set of all points reachable with some control
input
reachable set
starting at a point in the state space
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Backwards Reachable Set
set of all states that can reach the final point
for some control input
backwards reachable set
given a final point in the state space
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Backwards Reachable Set
Backwards reachable set
No-fly zone
States that can reach the no-fly zone when
control is applied
Can prevent aircraft from entering no-fly zone
Safe States
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Implicit Surface Functions
implicit surface function for no-fly zone
implicit surface function for backwards reachable
set
No-fly zone
Backwards Reachable Set
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Analytic Solution

• Hamilton-Jacobi-Isaacs PDE

backwards reachable set implicit surface function
no-fly zone implicit surface function

• Evans Souganidis--1984
• v

dynamics
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Control from Implicit Surface Function
Control decreases to zero
Safe States
Safe States
Control at boundary
Backwards Reachable Set
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Numerical Solution

• Mitchell--2001

computations storage
1
2
3
4
states
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Get Real

• Control algorithm
• model predictive control

Richard Murray DARPA SEC Program Software Enabled
Control
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Conclusions

• Embedded control system challenge
• Control theory identified
• Future implementation challenges identified

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Acknowledgements

• Iman Ahmadi
• Zhongning Chen
• Xiaojun Liu
• Steve Neuendorffer
• Claire Tomlin