TY - GEN
T1 - Resilient control and safety for cyber-physical systems
AU - Lukina, Anna
AU - Tiwari, Ashish
AU - Smolka, Scott A.
AU - Esterle, Lukas
AU - Yang, Junxing
AU - Grosu, Radu
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/7
Y1 - 2018/8/7
N2 - Many Cyber-Physical Systems (CPSs) are comprising a multitude of computing entities that can collectively exhibit an emergent behavior. A compelling example of such systems is the drone swarm, which are beginning to see increasing application in battlefield surveillance and reconnaissance. The emergent behavior they exhibit is that of flight formation. A particularly interesting flight configuration is V-formation, especially for long-range missions. V-formation is emblematic of migratory birds such as Canada geese, where a bird flying in the upwash region of the bird in front of it can enjoy significant energy savings. In addition, the V-formation offers a clear view benefit, as no bird's field of vision is obstructed by another bird in the formation. Hence, it is important to quantify the resiliency of the control algorithms underlying this class of CPSs to various kinds of attacks. This question provides the motivation for the investigation put forth in this abstract and detailed in [4].
AB - Many Cyber-Physical Systems (CPSs) are comprising a multitude of computing entities that can collectively exhibit an emergent behavior. A compelling example of such systems is the drone swarm, which are beginning to see increasing application in battlefield surveillance and reconnaissance. The emergent behavior they exhibit is that of flight formation. A particularly interesting flight configuration is V-formation, especially for long-range missions. V-formation is emblematic of migratory birds such as Canada geese, where a bird flying in the upwash region of the bird in front of it can enjoy significant energy savings. In addition, the V-formation offers a clear view benefit, as no bird's field of vision is obstructed by another bird in the formation. Hence, it is important to quantify the resiliency of the control algorithms underlying this class of CPSs to various kinds of attacks. This question provides the motivation for the investigation put forth in this abstract and detailed in [4].
KW - Flocking
KW - Model-predictive-control
KW - Resiliency
KW - Statistical-model-checking
KW - V-formation
UR - https://www.scopus.com/pages/publications/85052520979
U2 - 10.1109/MT-CPS.2018.00015
DO - 10.1109/MT-CPS.2018.00015
M3 - Conference contribution
AN - SCOPUS:85052520979
SN - 9781538667484
T3 - Proceedings - 2018 3rd Workshop on Monitoring and Testing of Cyber-Physical Systems, MT-CPS 2018
SP - 16
EP - 17
BT - Proceedings - 2018 3rd Workshop on Monitoring and Testing of Cyber-Physical Systems, MT-CPS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd Workshop on Monitoring and Testing of Cyber-Physical Systems, MT-CPS 2018
Y2 - 10 April 2018
ER -