Distributed discrete-time optimization of heterogeneous multi-agent networks with unbounded position constraints and nonconvex velocity constraints

摘要

The distributed discrete-time heterogeneous multi-agent optimization problem with unbounded position constraints and nonconvex velocity constraints was considered in this paper, where the models of agents are described by first-or second-order difference equations, the position constraints are assumed to be unbounded and convex and the velocity constraints are assumed to be bounded, closed and non convex. An improved distributed algorithm is adopted, under which, all agents could collaboratively minimize the entire objective function and the positions and velocities could always stay at the corresponding constraint sets. Then the convergence analysis is completed by the coordination transformation and the properties of projection operator and constraint operator. Finally, we give examples to illustrate the correctness of results. (c) 2021 Elsevier B.V. All rights reserved.