Distributed optimization for uncertain Euler–Lagrange Systems with local and relative measurements

This paper considers a multi-agent system modeled as a group of Euler–Lagrange systems, and assumes that each agent only has perception of the real-time position-dependent gradient value of a local objective function and its relative position with other agents. Based on a seamless integration of a m...

Full description

Saved in:
Bibliographic Details
Published in:Automatica (Oxford) Vol. 139; p. 110113
Main Authors: Qin, Zhengyan, Jiang, Liangze, Liu, Tengfei, Jiang, Zhong-Ping
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.05.2022
Subjects:
Distributed optimization
Euler–Lagrange systems
Relative measurements
Uncertainties
Distributed optimization
Relative measurements
Euler–Lagrange systems
Uncertainties
ISSN:0005-1098
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper considers a multi-agent system modeled as a group of Euler–Lagrange systems, and assumes that each agent only has perception of the real-time position-dependent gradient value of a local objective function and its relative position with other agents. Based on a seamless integration of a modified distributed optimization algorithm and a Lyapunov-based nonlinear control design, distributed controllers are developed to exponentially steer the position of each agent to the optimal point of the total objective function. A numerical example of coordinated communication relay is employed to verify the proposed design.
ISSN:0005-1098
DOI:10.1016/j.automatica.2021.110113