Distributed Strategies for Constrained Nonsmooth Resource Allocation Problems With Autonomous Second-Order Agents

In this paper, constrained nonsmooth resource allocation problems (RAPs) of autonomous agents are investigated. All agents are subject to inequality network resource constraints and local constraints, and each agent has a nonsmooth private payoff function in our problem. Furthermore, in contrast to...

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Published inIEEE transactions on network science and engineering Vol. 11; no. 3; pp. 2927 - 2936
Main Authors Deng, Zhenhua, Chen, Tao
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.05.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Constraints
Convergence
Couplings
Cyber-physical systems
distributed strategies
Game theory
Inequality
Manganese
Multi-agent systems
Nonlinear dynamics
nonsmooth optimization
Optimization
Resource allocation
Resource management
Second-order multi-agent systems
State feedback
Wireless networks
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Abstract In this paper, constrained nonsmooth resource allocation problems (RAPs) of autonomous agents are investigated. All agents are subject to inequality network resource constraints and local constraints, and each agent has a nonsmooth private payoff function in our problem. Furthermore, in contrast to the well-known RAPs, all agents have second-order linear/nonlinear (SOL/SON) dynamics, which means that there is no way to directly control the actions of agents in our problem. To the best of our knowledge, there are no results on nonsmooth RAPs of autonomous SOL/SON agents, let alone involving inequality constraints. Existing related distributed strategies cannot solve our problem, due to the presence of SOL/SON dynamics, nonsmooth payoff functions, and/or inequality constraints. We put forward two fully distributed subgradient-based strategies on the basis of state feedback and primal-dual methods for SOL and SON agents, respectively. By our strategies, all agents rely only on local information to update their control inputs, compared with existing RAPs with physical systems. We analyze the two strategies using nonsmooth analysis and the set-valued Lasalle invariance principle. Under our strategies, the SOL/SON agents globally converge to the optimal allocation (OA). Finally, numerical simulations demonstrate our strategies.
AbstractList In this paper, constrained nonsmooth resource allocation problems (RAPs) of autonomous agents are investigated. All agents are subject to inequality network resource constraints and local constraints, and each agent has a nonsmooth private payoff function in our problem. Furthermore, in contrast to the well-known RAPs, all agents have second-order linear/nonlinear (SOL/SON) dynamics, which means that there is no way to directly control the actions of agents in our problem. To the best of our knowledge, there are no results on nonsmooth RAPs of autonomous SOL/SON agents, let alone involving inequality constraints. Existing related distributed strategies cannot solve our problem, due to the presence of SOL/SON dynamics, nonsmooth payoff functions, and/or inequality constraints. We put forward two fully distributed subgradient-based strategies on the basis of state feedback and primal-dual methods for SOL and SON agents, respectively. By our strategies, all agents rely only on local information to update their control inputs, compared with existing RAPs with physical systems. We analyze the two strategies using nonsmooth analysis and the set-valued Lasalle invariance principle. Under our strategies, the SOL/SON agents globally converge to the optimal allocation (OA). Finally, numerical simulations demonstrate our strategies.
Author Chen, Tao
Deng, Zhenhua
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Snippet In this paper, constrained nonsmooth resource allocation problems (RAPs) of autonomous agents are investigated. All agents are subject to inequality network...
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SubjectTerms Constraints
Convergence
Couplings
Cyber-physical systems
distributed strategies
Game theory
Inequality
Manganese
Multi-agent systems
Nonlinear dynamics
nonsmooth optimization
Optimization
Resource allocation
Resource management
Second-order multi-agent systems
State feedback
Wireless networks
Title Distributed Strategies for Constrained Nonsmooth Resource Allocation Problems With Autonomous Second-Order Agents
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Volume 11
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