On distributed constrained formation control in operator–vehicle adversarial networks

We consider an operator–vehicle network where each vehicle is remotely maneuvered by an operator. The objective of the operators is to steer the vehicles to the desired formation subject to the given state and input constraints. Each operator–vehicle pair is attacked by an adversary who is able to m...

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Bibliographic Details
Published in:Automatica (Oxford) Vol. 49; no. 12; pp. 3571 - 3582
Main Authors: Zhu, Minghui, Martínez, Sonia
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.12.2013
Elsevier
Subjects:
Algorithms
Applied sciences
Asymptotic properties
Commands
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Constraints
Control theory. Systems
Distributed control
Exact sciences and technology
Memory and file management (including protection and security)
Memory organisation. Data processing
Multi-agent systems
Networks
Operators
Resilience
Resilient control
Robotics
Software
Vehicles
Distributed control
Resilient control
Multi-agent systems
Motor car
Local network
Constrained optimization
Resilience
Model predictive control
Control constraint
Multiagent system
Distributed algorithm
Cryptanalysis
Asymptotic approximation
Replay attack
Denial of service
Open ended horizon
Formation
Computer security
State constraint
ISSN:0005-1098, 1873-2836
Online Access:Get full text
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Summary:We consider an operator–vehicle network where each vehicle is remotely maneuvered by an operator. The objective of the operators is to steer the vehicles to the desired formation subject to the given state and input constraints. Each operator–vehicle pair is attacked by an adversary who is able to maliciously replay the control commands sent from the operator. To play against attackers, we come up with a novel distributed resilient algorithm based on the receding-horizon control methodology, and show that the algorithm is able to allow vehicles, on the one hand, satisfy state and input constraints, and on the other hand, asymptotically achieve the desired formation despite replay attacks. With slight modifications, our proposed algorithm shows an analogous resilience to denial-of-service attacks.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2013.09.031