TY - GEN
T1 - Entropy-Based Health State Evaluation of Unmanned Cluster Systems
AU - Kong, Linghao
AU - Wang, Lizhi
AU - Wang, Xiaohong
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - Unmanned cluster system refers to an overall system in which a number of unmanned systems cooperate to accomplish complex tasks in a certain time and space according to the division of tasks. In recent years, the technology of unmanned cluster system has been gradually intelligent and the application has been gradually open, and its health state is dynamic and changeable, and the health state assessment of unmanned cluster system faces new problems. To address this problem, this study analyzes the current health state elements of unmanned cluster systems, and divides them into three levels: topology, traffic, and task. And based on the characteristics of unmanned cluster system, the system was modeled as a multi-layer complex network. The health state indicators were constructed through the theory of reliability entropy and group entropy combined with the physical characteristics of clusters. The health state assessment of unmanned cluster system was carried out by using the entropy indexes, and finally, the method was verified by simulation cases, which were analyzed by Wiener process simulation and multi-intelligence body simulation to better guide the health state assessment of unmanned cluster system in practical applications.
AB - Unmanned cluster system refers to an overall system in which a number of unmanned systems cooperate to accomplish complex tasks in a certain time and space according to the division of tasks. In recent years, the technology of unmanned cluster system has been gradually intelligent and the application has been gradually open, and its health state is dynamic and changeable, and the health state assessment of unmanned cluster system faces new problems. To address this problem, this study analyzes the current health state elements of unmanned cluster systems, and divides them into three levels: topology, traffic, and task. And based on the characteristics of unmanned cluster system, the system was modeled as a multi-layer complex network. The health state indicators were constructed through the theory of reliability entropy and group entropy combined with the physical characteristics of clusters. The health state assessment of unmanned cluster system was carried out by using the entropy indexes, and finally, the method was verified by simulation cases, which were analyzed by Wiener process simulation and multi-intelligence body simulation to better guide the health state assessment of unmanned cluster system in practical applications.
KW - Indicator evaluation
KW - complex network
KW - entropy
KW - health state
KW - unmanned cluster system
UR - https://www.scopus.com/pages/publications/85199353605
U2 - 10.1007/978-981-97-3332-3_12
DO - 10.1007/978-981-97-3332-3_12
M3 - 会议稿件
AN - SCOPUS:85199353605
SN - 9789819733316
T3 - Lecture Notes in Electrical Engineering
SP - 128
EP - 138
BT - Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Perception and Navigation Technologies
A2 - Yu, Jianglong
A2 - Li, Qingdong
A2 - Liu, Yumeng
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023
Y2 - 24 November 2023 through 27 November 2023
ER -