A distributed resource allocation problem of high-order systems is studied in this article, where the decisions of agents are constrained by network resources. In contrast to well-known resource allocation problems, this problem involves the high-order dynamics of agents, which results in the ineffectiveness of existing distributed resource allocation algorithms. In order to optimally allocate the network resource, a distributed algorithm is developed via state feedback and gradient descent. Moreover, the convergence of the algorithm is analyzed with the help of convex analysis and Lyapunov stability theory. By the algorithm, the high-order agents globally exponentially converge to the optimal solution. Finally, the algorithm is illustrated by numerical examples.

中文翻译：

---

高阶多主体系统资源分配问题的分布式算法设计

本文研究了高阶系统的分布式资源分配问题，其中代理的决策受网络资源的约束。与众所周知的资源分配问题相反，此问题涉及代理的高阶动态，这导致现有的分布式资源分配算法无效。为了优化分配网络资源，通过状态反馈和梯度下降开发了一种分布式算法。此外，借助凸分析和Lyapunov稳定性理论对算法的收敛性进行了分析。通过该算法，高阶智能体全局指数收敛于最优解。最后，通过数值例子说明了该算法。