Distributed Optimization for Continuous Time Multiple Agents Systems With Unknown Parameters

This paper addresses a distributed convex optimization problem with objective functions for arbitrary order continuous time multiply agents systems with unknown parameters. In this paper, the control objective is not only to drive the multiply agents to reach a consensus, but also to cooperatively minimize the team objective function with consensus requirement. Different from the traditional optimization problems, in this paper, the proposed method is distributed, which means that the agent can only acquire the information of its neighbors' objective function through the network connection. Theoretical studies indicate that the proposed algorithms can minimize the team objective function and all agents will reach a consensus. Some simulation examples are presented to show the validity of the theoretical results.