This article studies the problem of distributed adaptive cooperative tracking for multiagent systems with communication constraints in complex communication environments. For this problem, a novel quantitative adaptive tracking control strategy is proposed based on adaptive backstepping technology, quantization theory, and variable transformation. First, the mechanism of communication between agents or between agents and ground stations is analyzed and quantized. And a multiagent swarm formation model with quantized inputs is established by considering a class of high-order nonlinear multiagent systems with partially unknown parameters. Moreover, the limitation of the nonholonomic constraint is removed via the variable transformation method. The adaptive backstepping method is used to design an adaptive cooperative tracking controller to update the unknown parameters of the model in real-time. Formation flight is maintained by designing time-varying reference trajectories to track the desired specified positions. Then, the rationality of the proposed method is verified in terms of Lyapunov stability. Finally, the designed control strategy is applied to a scaled-down model for an unmanned aerial vehicle formation to further verify its effectiveness in practical engineering applications.

中文翻译：

---

通信约束下多智能体编队的自适应分布式协作跟踪控制及应用


本文研究复杂通信环境下具有通信约束的多智能体系统的分布式自适应协作跟踪问题。针对该问题，基于自适应反步技术、量化理论和变量变换，提出了一种新颖的定量自适应跟踪控制策略。首先，对智能体之间或智能体与地面站之间的通信机制进行分析和量化。考虑一类部分未知参数的高阶非线性多智能体系统，建立了具有量化输入的多智能体群体形成模型。此外，通过变量变换方法消除了非完整约束的限制。采用自适应反步法设计自适应协作跟踪控制器，实时更新模型的未知参数。通过设计随时间变化的参考轨迹来跟踪所需的指定位置来维持编队飞行。然后，从Lyapunov稳定性方面验证了所提方法的合理性。最后，将设计的控制策略应用于无人机编队缩小模型，进一步验证其在实际工程应用中的有效性。