Adaptive Collaborative Control of Multiagent Systems by Event-Triggered Mechanisms (Intelligent Control and Learning Systems, 14)

Adaptive Collaborative Control of Multiagent Systems by Event-Triggered Mechanisms (Intelligent Control and Learning Systems, 14)

Adaptive Collaborative Control of Multiagent Systems by Event-Triggered Mechanisms (Intelligent Control and Learning Systems, 14)

by: Juan Zhang (Author), Huaguang Zhang (Author), Dongsheng Yang (Author), Yanhong Luo (Author), Bowen Zhou (Author)

Publisher: Springer

Edition: 2024th

Publication Date: 2025-02-22

Language: English

Print Length: 209 pages

ISBN-10: 9819778654

ISBN-13: 9789819778652

Book Description

This book provides a detailed study of several types of control problems in multi-agent systems, including consensus, output regulation, containment, and formation problems. The research on collaborative control of multi-agent systems has attracted engineers and scientists from various disciplines such as control, mathematics, artificial intelligence, and computer engineering. This book proposes a control strategy based on adaptive triggering mechanism and establishes a basic energy-saving framework; it also proposes an adaptive learning rate to replace fixed weights, ensuring that the proposed strategy does not rely on any global information of the communication topology and has scalability. This book is ideal for students, researchers, and engineers in collaborative control, wireless networks, power grids, UAVs, and more.

Editorial Reviews

This book provides a detailed study of several types of control problems in multi-agent systems, including consensus, output regulation, containment, and formation problems. The research on collaborative control of multi-agent systems has attracted engineers and scientists from various disciplines such as control, mathematics, artificial intelligence, and computer engineering. This book proposes a control strategy based on adaptive triggering mechanism and establishes a basic energy-saving framework; it also proposes an adaptive learning rate to replace fixed weights, ensuring that the proposed strategy does not rely on any global information of the communication topology and has scalability. This book is ideal for students, researchers, and engineers in collaborative control, wireless networks, power grids, UAVs, and more.

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