Distributed predefined-time constrained social cost minimization problem under the partial information setting

Abstract

In this letter, the social cost minimization problem with coupled equality constraints is studied, where the agents endeavor to collaboratively minimize the sum of all local cost functions, and each local cost function depends on a global decision variable consisting of the decisions of all participants. In a setting where only partial information about one’s own decisions and cost function is available, the first single-time scale predefined-time distributed algorithm based on the time-based-generator scheme is designed to tackle the problem. With the help of the Lyapunov stability theory, it is demonstrated that the algorithm can converge to the optimal solution in an arbitrarily specified time independent of the initial state and control parameters. Finally, the effectiveness of the proposed algorithm is verified by numerical simulations.