Paper Info
Title
Distributed extremum seeking control of multi-agent systems with unknown dynamics for optimal resource allocation.
Abstract
The paper considers a class of equality constrained resource allocation problems for dynamically coupled multi-agent systems. It is assumed that the mathematical structure of each agent’s dynamics and its local cost function are unknown but depend on the entire resource allocation vector. A distributed dual-mode extremum seeking control is proposed. It is shown that the distributed approach decouples the local contribution of each agent locally while guaranteeing a solution of the network wide optimization problem subject to the resource allocation constraints. The agents operate over a communication network which enables the application of a dynamic consensus algorithm to generate local estimates of the total network cost. Locally, each agent implements a parameter estimation routine to estimate the gradient of the total cost with respect to the local action. Each agent uses its local gradient estimate to implement a dual mode extremum seeking controller that guarantees satisfaction of the resource allocation constraints. Two simulation examples are provided to demonstrate the effectiveness of the proposed technique.
Year
DOI
Venue
2020
10.1016/j.neucom.2019.11.086
Neurocomputing
Keywords
Field
DocType
Communication network,Consensus estimation,Distributed control,Extremum seeking control,Gradient estimation,Multi-agent systems,Real-time optimization,Resource allocation
Control theory,Mathematical optimization,Telecommunications network,Mathematical structure,Multi-agent system,Resource allocation,Artificial intelligence,Estimation theory,Total cost,Optimization problem,Mathematics,Machine learning
Journal
Volume
ISSN
Citations 
381
0925-2312
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Judith Ogwuru100.34
M. Guay228341.27