TY - GEN
T1 - Joint task management of sensor and weapon based on distributed management system
AU - Zhang, Mingyang
AU - Chen, Chen
N1 - Publisher Copyright:
© 2017 Technical Committee on Control Theory, CAA.
PY - 2017/9/7
Y1 - 2017/9/7
N2 - In the modern war, many combat units combat collectively has become the main form. In the task management of the combat units, the calculation is large and the real-time requirement is high. To solve the problem better, a joint task management method of sensor and weapon based on distributed management system is proposed. Firstly, the distributed management system is constructed according to the target trajectory and the distribution of combat units. In the system, all the combat units are divided into several combinations, which only consist of a few combat units. As a result, the problem scale is reduced, and the real-time requirement of battlefield is met. Secondly, joint task management model of sensor and weapon is established. We consider time constraints and resource constraints to ensure the feasibility of the attack scheme, and consider the impact between sensor and weapon to achieve better combat effect. A discrete particle swarm optimization algorithm based on crossover strategy (CDPSO) is proposed to solve the model. The results show that the performance of the proposed algorithm is satisfactory in joint task management of sensor and weapon.
AB - In the modern war, many combat units combat collectively has become the main form. In the task management of the combat units, the calculation is large and the real-time requirement is high. To solve the problem better, a joint task management method of sensor and weapon based on distributed management system is proposed. Firstly, the distributed management system is constructed according to the target trajectory and the distribution of combat units. In the system, all the combat units are divided into several combinations, which only consist of a few combat units. As a result, the problem scale is reduced, and the real-time requirement of battlefield is met. Secondly, joint task management model of sensor and weapon is established. We consider time constraints and resource constraints to ensure the feasibility of the attack scheme, and consider the impact between sensor and weapon to achieve better combat effect. A discrete particle swarm optimization algorithm based on crossover strategy (CDPSO) is proposed to solve the model. The results show that the performance of the proposed algorithm is satisfactory in joint task management of sensor and weapon.
KW - CDPSO
KW - distributed management system
KW - join task management
KW - resource constraints
KW - time constraints
UR - http://www.scopus.com/inward/record.url?scp=85032178466&partnerID=8YFLogxK
U2 - 10.23919/ChiCC.2017.8027820
DO - 10.23919/ChiCC.2017.8027820
M3 - Conference contribution
AN - SCOPUS:85032178466
T3 - Chinese Control Conference, CCC
SP - 3002
EP - 3007
BT - Proceedings of the 36th Chinese Control Conference, CCC 2017
A2 - Liu, Tao
A2 - Zhao, Qianchuan
PB - IEEE Computer Society
T2 - 36th Chinese Control Conference, CCC 2017
Y2 - 26 July 2017 through 28 July 2017
ER -