Distributed Optimal Formation for Uncertain Euler-Lagrange Systems With Collision Avoidance

Based on the framework of distributed optimization algorithms, this brief studies distributed optimal formation behaviors of multi-agent systems modeled as a group of uncertain Euler-Lagrange systems with collision avoidance. Assume that each agent can only obtain measured position-based gradient value of a local objective function. By integrating a modified distributed optimization algorithm and an adaptive control law, the proposed distributed optimal formation controllers can lead the positions of agents asymptotically converging to the optimal solution to the total objective function with collision avoidance. The proposed design is verified by a numerical example of mobile relays for communication.