Noncooperative Game of Distributed Quadrotor UAVs With Multiple Constraints

• Published in: IEEE transactions on aerospace and electronic systems Vol. 60; no. 4; pp. 4728 - 4739
• Main Authors: Geng, Mei-Jie, Ding, Hua-Feng, Yao, Xiang-Yu, Liu, Wen-Jin, Hua, Menghu
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Algorithms; Asymptotic methods; Autonomous aerial vehicles; Communications systems; Constraints; Effectiveness; Equilibrium; Fault tolerance; Fault tolerant systems; Fault-tolerant algorithm; Game theory; Games; generalized Nash equilibrium; Heuristic algorithms; Markov process; Nash equilibrium; noncooperative game; Parameter uncertainty; quadrotor unmanned aerial vehicles (UAVs); Quadrotors; Task analysis; Unmanned aerial vehicles; Unmanned helicopters; Virtual networks
• ISSN: 0018-9251; 1557-9603
• DOI: 10.1109/TAES.2024.3383418

This article studies the noncooperative game of distributed quadrotor unmanned aerial vehicles (UAVs) under task, communication, and physical constraints. Compared to existing works that primarily focus on the flight task of Nash equilibrium seeking without task constraints or only with equality constraints, this study considers a noncooperative game with inequality constraints. To enhance the privacy of quadrotor UAVs communications, Markov jump networks are introduced as communication constraints to increase the stochasticity of the distributed system and all agents can search the Nash equilibrium by sharing virtual information. Furthermore, an effective fault-tolerant algorithm is proposed to address physical constraints, enabling all quadrotor UAVs to reach the generalized Nash equilibrium states subject to actuator faults, uncertain dynamic parameters, and time-varying disturbances. Then, the asymptotic stability of the proposed algorithms is proved by the projected gradient descent methodology and Lyapunov techniques. Finally, some simulations are conducted to verify the effectiveness of the suggested algorithms.