A Specified-Time Distributed Optimization Algorithm for Multiagent Systems With Time-Varying Constraints

Abstract

In this article, a class of distributed optimization problems for multiagent systems subject to time-varying coupling equality constraint is investigated. The global objective function is a sum of local convex objective functions and only local information is exchanged among the agents over a connected and undirected communication network. Based on convex optimization and Lyapunov stability theory, we show that the multiagent system in closed loop with the proposed distributed protocol is able to converge to the time-dependent unique optimum within a specified time. Remarkably, the convergence time is independent of the initial conditions and can be specified in advance making the proposed scheme suitable for application with strict requirements on the convergence. We validate through simulations the effectiveness of the theoretical results.