학술논문

Generalized Second-Order Neurodynamic Approach for Distributed Optimal Allocation
Document Type
Periodical
Source
IEEE Transactions on Systems, Man, and Cybernetics: Systems IEEE Trans. Syst. Man Cybern, Syst. Systems, Man, and Cybernetics: Systems, IEEE Transactions on. 54(6):3369-3380 Jun, 2024
Subject
Signal Processing and Analysis
Robotics and Control Systems
Power, Energy and Industry Applications
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Neurodynamics
Resource management
Switches
Topology
Multi-agent systems
Dynamic scheduling
Dynamics
Distributed optimal allocation
generalized second-order neurodynamic approach
multiagent system
resource interactions
switching communication topologies
Language
ISSN
2168-2216
2168-2232
Abstract
In this article, based on the multiagent system with second-order dynamics, two neurodynamic approaches are proposed to solve the distributed optimal allocation problem (DOAP) with equality resource interaction, inequality resource interaction, and local feasible constraints.over the switching communication topologies. To address the equality and inequality resource interactions in a distributed way, the corresponding auxiliary variables are introduced to ensure the local estimations of Lagrangian multipliers reach consensus in a distributed manner. On this basis, a novel generalized second-order neurodynamic approach is presented to solve the nonsmooth DOAP, and the theoretical proof of convergence is provided. Furthermore, to prevent global information from being involved, another generalized second-order neurodynamic approach is designed and its effectiveness is also analyzed. Finally, a numerical example and an application of the maximum network utility problem are simulated to verify the correctness of the conclusions.