Optimization Control for Multiagent Systems with Disturbances via Dynamic Triggered Mechanisms

Yuanshan Liu

ISBN 10: 999931466X / ISBN 13: 9789999314664

Verlag: Eliva Press Jan 2024, 2024

Beschreibung

Neuware -In this comprehensive study on distributed optimization in multiagent systems, the authors present a pioneering approach to managing external disturbances in complex network scenarios. This book addresses the challenges in systems with both fixed and switching topologies, introducing an innovative controller equipped with dynamic triggered mechanisms. These mechanisms are expertly designed to reduce communication resource waste and lower agent energy consumption significantly. Alongside, a novel distributed disturbance observer is developed to accurately estimate external disturbances in the input channels. The authors skillfully derive sufficient conditions for achieving consensus in multiagent systems under diverse network conditions. A key highlight is the successful avoidance of Zeno behaviors by the designed mechanisms, marking a significant advancement in the field. The effectiveness of these groundbreaking algorithms is further underscored through rigorous numerical simulations. This book is a critical resource for anyone interested in the forefront of research in dynamic systems and control theory, offering both theoretical depth and practical insights.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 50 pp. Englisch. Bestandsnummer des Verkäufers 9789999314664

Bibliografische Details

Titel: Optimization Control for Multiagent Systems ...

Verlag: Eliva Press Jan 2024

Erscheinungsdatum: 2024

Einband: Taschenbuch

Zustand: Neu

Über diesen Titel

Inhaltsangabe:

In this comprehensive study on distributed optimization in multiagent systems, the authors present a pioneering approach to managing external disturbances in complex network scenarios. This book addresses the challenges in systems with both fixed and switching topologies, introducing an innovative controller equipped with dynamic triggered mechanisms. These mechanisms are expertly designed to reduce communication resource waste and lower agent energy consumption significantly. Alongside, a novel distributed disturbance observer is developed to accurately estimate external disturbances in the input channels. The authors skillfully derive sufficient conditions for achieving consensus in multiagent systems under diverse network conditions. A key highlight is the successful avoidance of Zeno behaviors by the designed mechanisms, marking a significant advancement in the field. The effectiveness of these groundbreaking algorithms is further underscored through rigorous numerical simulations. This book is a critical resource for anyone interested in the forefront of research in dynamic systems and control theory, offering both theoretical depth and practical insights.