TY - GEN
T1 - Robust Cooperative Pursuit-Evasion Problem for Multiple Evaders and Pursuers with Measuring Noise
AU - Shi, Weixiang
AU - Wang, Chunyan
AU - Wang, Jianan
AU - Shan, Jiayuan
N1 - Publisher Copyright:
© 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - This paper addresses the robust cooperative pursuit-evasion problem for multiple evaders and pursuers in a bounded area with measuring noise. First, by considering the priorities of the evaders and the distances between the evaders and the pursuers, a choosing strategy is proposed for the pursuers to choose an appropriate evader as target in each period. Then, set-membership filter technique is used to deal with the measuring noise effect and the evader’s true position is estimated in an updated ellipsoid area. In particular, the ellipsoid area will reduce gradually when the pursuers come near to the evader. Finally, optimal control law is designed for each pursuer with the area-minimization policy, which guarantees that the evaders could be captured one by one in finite time. Simulation results verify the effectiveness of cooperative pursuit algorithm.
AB - This paper addresses the robust cooperative pursuit-evasion problem for multiple evaders and pursuers in a bounded area with measuring noise. First, by considering the priorities of the evaders and the distances between the evaders and the pursuers, a choosing strategy is proposed for the pursuers to choose an appropriate evader as target in each period. Then, set-membership filter technique is used to deal with the measuring noise effect and the evader’s true position is estimated in an updated ellipsoid area. In particular, the ellipsoid area will reduce gradually when the pursuers come near to the evader. Finally, optimal control law is designed for each pursuer with the area-minimization policy, which guarantees that the evaders could be captured one by one in finite time. Simulation results verify the effectiveness of cooperative pursuit algorithm.
KW - Area-minimization policy
KW - Cooperative pursuit-evasion
KW - Measuring noise
KW - Set-membership filter
UR - http://www.scopus.com/inward/record.url?scp=85120607179&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-8155-7_339
DO - 10.1007/978-981-15-8155-7_339
M3 - Conference contribution
AN - SCOPUS:85120607179
SN - 9789811581540
T3 - Lecture Notes in Electrical Engineering
SP - 4065
EP - 4074
BT - Advances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020
A2 - Yan, Liang
A2 - Duan, Haibin
A2 - Yu, Xiang
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Guidance, Navigation and Control, ICGNC 2020
Y2 - 23 October 2020 through 25 October 2020
ER -