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A Distributed Dynamical System for Optimal Resource Allocation Over State-Dependent Networks

Xiaoxuan Wang, Shaofu Yang, Zhenyuan Guo, Mengke Lian, Tingwen Huang

2022IEEE Transactions on Network Science and Engineering31 citationsDOI

Abstract

This paper focuses on investigating the nonsmooth resource allocation problem based on distributed dynamical systems over state-dependent communication networks. Taking into account the coupling of supply-demand constraint, a potential-based Lagrangian function containing local multipliers is reformulated by the exact penalty method. By virtue of the primal-dual subgradient flow, a distributed differentiated projected dynamical system with a state-dependent gain is proposed. It is shown that the connectivity of communication networks can be preserved under the proposed system. Furthermore, it is proved that the system converges to the optimal resource allocation with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {O}(1/t)$</tex-math></inline-formula> convergence rate. Finally, the theoretical results are substantiated through simulations of economic dispatch problems in the IEEE 30-bus system and IEEE 118-bus system.

Topics & Concepts

Subgradient methodMathematical optimizationResource allocationConstraint (computer-aided design)State (computer science)Convergence (economics)Computer scienceProjected dynamical systemFunction (biology)Distributed algorithmNotationDynamical systems theoryDistributed computingTopology (electrical circuits)MathematicsAlgorithmComputer networkLinear dynamical systemCombinatoricsRandom dynamical systemBiologyGeometryEconomic growthArithmeticEvolutionary biologyPhysicsEconomicsQuantum mechanicsDistributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationSmart Grid Energy Management