Abstract
In this paper, we investigate distributed resource allocation problems of second-order multi-agent systems, where the decisions of agents are subjected to inequality network resource constraints. In contrast to well-known resource allocation problems, the second-order dynamics of agents and the coupling inequality constraints are considered in our problem at the same time. 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 second-order agents globally asymptotically converge to the optimal solution. Finally, the effectiveness of our method is verified by the numerical example.
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