Open AccessEnergy-aware Distributed Formation Control for Multiple Unmanned Vehicles
Author(s) -
Qiyue Xie,
Yaoxin Xia,
Zhe Wang,
Jianjie Zhang,
Delei Kong,
Heng Li
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2203/1/012016
Subject(s) - overtaking , computer science , matlab , energy consumption , battery (electricity) , control (management) , energy (signal processing) , action (physics) , distributed computing , power (physics) , control engineering , simulation , artificial intelligence , engineering , electrical engineering , mathematics , statistics , civil engineering , physics , quantum mechanics , operating system
Multi-agent system is an important branch of distributed artificial intelligence. As a new field of engineering control science, it has developed vigorously in recent years. From a practical point of view, most existing agents, such as unmanned vehicles and unmanned aerial vehicles, are powered by mobile power supply. Therefore, it is of practical significance to consider the battery state and explore how to improve the overall battery life when designing the multi-agent control strategy. In this paper, we first introduced a classical algorithm based on the consensus theory, and on this basis, the overtaking action in the formation is realized by changing the topology, so as to simulate the individuals (action individuals) who consume more energy in the formation; then we discussed how to improve the endurance of high-energy-consuming individuals in formation through average energy consumption in strategy design, and proposed an algorithm based on energy-aware. Finally, the MATLAB simulation results show that compared with the classical algorithm, the proposed algorithm can improve the endurance of formation.