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...

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Veröffentlicht in:Automatica (Oxford) Jg. 139; S. 110113
Hauptverfasser: Qin, Zhengyan, Jiang, Liangze, Liu, Tengfei, Jiang, Zhong-Ping
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.05.2022
Schlagworte:
Distributed optimization
Euler–Lagrange systems
Relative measurements
Uncertainties
Distributed optimization
Relative measurements
Euler–Lagrange systems
Uncertainties
ISSN:0005-1098
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Zusammenfassung: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