TY - JOUR
T1 - On distributed constrained formation control in operator-vehicle adversarial networks
AU - Zhu, Minghui
AU - Martínez, Sonia
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013/12
Y1 - 2013/12
N2 - 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.
AB - 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.
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U2 - 10.1016/j.automatica.2013.09.031
DO - 10.1016/j.automatica.2013.09.031
M3 - Article
AN - SCOPUS:84887989273
VL - 49
SP - 3571
EP - 3582
JO - Automatica
JF - Automatica
SN - 0005-1098
IS - 12
ER -