Weighted Multi-Game Approach to Multi-QUAV Formation Control

In this paper, a weighted multi-game control method is proposed for the multi-Quadrotor Unmanned Aerial Vehicle(QUAV) formation problem. First, an objective function describing the formation mission accomplishment is designed for each QUAV in the system. Then, a game is established between two QUAVs that can communicate with each other. A set of strategies that minimize the value of the objective function of each of the two QUAVs participating in the game at the next decision-making are obtained through the established game. Since, each QUAV in the system may establish communication relationships with multiple QUAVs, multiple control strategies will be obtained when updating the control strategy through the game. Finally, the weights of the multiple control strategies obtained through the game are obtained based on the error relationship between each QUAV and the QUAVs that can establish communication with it. The actual control strategy of the QUAV can be obtained by weighted summation of multiple control strategies. And the feasibility of the method is proved by simulation experiments and hardware experiments.

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Publication Details

Published
2025-07-04
DOI
https://doi.org/10.1109/fasta65681.2025.11138746
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Weighted Multi-Game Approach to Multi-QUAV Formation Control

Yiqing Huang, Heming Huang, Fuxuan Cai
Target Tracking and Data Fusion in Sensor Networks
article

Weighted Multi-Game Approach to Multi-QUAV Formation Control

Yiqing Huang, Heming Huang, Fuxuan Cai
article en

Abstract

In this paper, a weighted multi-game control method is proposed for the multi-Quadrotor Unmanned Aerial Vehicle(QUAV) formation problem. First, an objective function describing the formation mission accomplishment is designed for each QUAV in the system. Then, a game is established between two QUAVs that can communicate with each other. A set of strategies that minimize the value of the objective function of each of the two QUAVs participating in the game at the next decision-making are obtained through the established game. Since, each QUAV in the system may establish communication relationships with multiple QUAVs, multiple control strategies will be obtained when updating the control strategy through the game. Finally, the weights of the multiple control strategies obtained through the game are obtained based on the error relationship between each QUAV and the QUAVs that can establish communication with it. The actual control strategy of the QUAV can be obtained by weighted summation of multiple control strategies. And the feasibility of the method is proved by simulation experiments and hardware experiments.

Anhui Polytechnic University (CN)
Openalex Percentile: Top 87%
Target Tracking and Data Fusion in Sensor Networks
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Weighted Multi-Game Approach to Multi-QUAV Formation Control — Yiqing Huang, Heming Huang, et al. · (2025) | TGRS Research Map | TGRS