Distributed Nonlinear Placement for Multicluster Systems: A Time-Varying Nash Equilibrium-Seeking Approach

In this article, a class of distributed nonlinear placement problems is considered for a multicluster system. The task is to determine the positions of the agents in each cluster subject to the constraints on agent positions and the network topology. In particular, the agents in each cluster are placed to form the desired shape and minimize the sum of squares of the Euclidean lengths of the links amongst the center of each cluster and its corresponding cluster members. The problem is converted into a time-varying noncooperative game and then a distributed Nash equilibrium-seeking algorithm is designed based on a distributed observer method. A new iterative approach is employed to prove the convergence with the aid of the Lyapunov stability theorem. The effectiveness of the distributed algorithm is validated by numerical examples.

Automated summary

This article examines a class of distributed nonlinear placement problems for a multicluster system, formulating the task as a time-varying noncooperative game and designing a distributed Nash equilibrium-seeking algorithm based on a distributed observer method. The effectiveness of the algorithm is validated through numerical examples, proving convergence using the Lyapunov stability theorem.