Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash Game

For the formation reconfiguration of fixed-wing unmanned aerial vehicles (UAVs), a hierarchical control decision-making method considering both convergence and optimality is studied. To begin with, the dynamic model of the fixed-wing UAVs is established, and the formation reconfiguration control pro...

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Main Authors: Hongxu Zhu, Shufan Wu
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Drones
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Online Access:https://www.mdpi.com/2504-446X/9/6/439
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author Hongxu Zhu
Shufan Wu
author_facet Hongxu Zhu
Shufan Wu
author_sort Hongxu Zhu
collection DOAJ
description For the formation reconfiguration of fixed-wing unmanned aerial vehicles (UAVs), a hierarchical control decision-making method considering both convergence and optimality is studied. To begin with, the dynamic model of the fixed-wing UAVs is established, and the formation reconfiguration control problem formally constructed. Subsequently, based on information such as the initial positions of the UAVs and the expected geometric configuration, an integer programming issue is formulated to determine the destinations of the UAVs. After completing the aforementioned preparations, by incorporating the concept of hierarchical games, the formation guidance and control problem is consequently reformulated as a multiplayer Stackelberg–Nash game (SNG). Through rigorous analysis, the optimality of using the Stackelberg–Nash equilibrium solution as the UAV control commands was demonstrated. Furthermore, a novel policy iteration (PI) algorithm for solving this equilibrium based on fixed-point iteration is proposed. To guarantee the accurate execution of the control commands, an auxiliary control system is designed, thereby forming a closed-loop real-time control decision-making mechanism. The numerical simulation results illustrate that the UAVs can rapidly switch to the desired formation configuration, thus validating the effectiveness of the proposed method.
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institution Kabale University
issn 2504-446X
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publishDate 2025-06-01
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series Drones
spelling doaj-art-7fb724fe9ea24c0ab8649a0e7efbe7ce2025-08-20T03:24:34ZengMDPI AGDrones2504-446X2025-06-019643910.3390/drones9060439Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash GameHongxu Zhu0Shufan Wu1School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, ChinaSchool of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, ChinaFor the formation reconfiguration of fixed-wing unmanned aerial vehicles (UAVs), a hierarchical control decision-making method considering both convergence and optimality is studied. To begin with, the dynamic model of the fixed-wing UAVs is established, and the formation reconfiguration control problem formally constructed. Subsequently, based on information such as the initial positions of the UAVs and the expected geometric configuration, an integer programming issue is formulated to determine the destinations of the UAVs. After completing the aforementioned preparations, by incorporating the concept of hierarchical games, the formation guidance and control problem is consequently reformulated as a multiplayer Stackelberg–Nash game (SNG). Through rigorous analysis, the optimality of using the Stackelberg–Nash equilibrium solution as the UAV control commands was demonstrated. Furthermore, a novel policy iteration (PI) algorithm for solving this equilibrium based on fixed-point iteration is proposed. To guarantee the accurate execution of the control commands, an auxiliary control system is designed, thereby forming a closed-loop real-time control decision-making mechanism. The numerical simulation results illustrate that the UAVs can rapidly switch to the desired formation configuration, thus validating the effectiveness of the proposed method.https://www.mdpi.com/2504-446X/9/6/439fixed-wing unmanned aerial vehiclesformation reconfiguration controlStackelberg–Nash gameoptimal feedback controlhierarchical control decision making
spellingShingle Hongxu Zhu
Shufan Wu
Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash Game
Drones
fixed-wing unmanned aerial vehicles
formation reconfiguration control
Stackelberg–Nash game
optimal feedback control
hierarchical control decision making
title Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash Game
title_full Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash Game
title_fullStr Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash Game
title_full_unstemmed Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash Game
title_short Leader–Follower Formation Reconfiguration Control for Fixed-Wing UAVs Using Multiplayer Stackelberg–Nash Game
title_sort leader follower formation reconfiguration control for fixed wing uavs using multiplayer stackelberg nash game
topic fixed-wing unmanned aerial vehicles
formation reconfiguration control
Stackelberg–Nash game
optimal feedback control
hierarchical control decision making
url https://www.mdpi.com/2504-446X/9/6/439
work_keys_str_mv AT hongxuzhu leaderfollowerformationreconfigurationcontrolforfixedwinguavsusingmultiplayerstackelbergnashgame
AT shufanwu leaderfollowerformationreconfigurationcontrolforfixedwinguavsusingmultiplayerstackelbergnashgame