東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Distributed cooperative control and ...

Wang, Qing.

Linked to FindBook

Google Book

Amazon

博客來

Distributed cooperative control and optimization for multi-agent systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Distributed cooperative control and optimization for multi-agent systems/ by Qing Wang, Bin Xin, Jie Chen.
Author:	Wang, Qing.
other author:	Xin, Bin.
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	ix, 149 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	Introduction -- Disturbance observer-based sliding mode control for multi-agent systems with mismatched uncertainties -- Observer-based containment for a class of nonlinear multi-agent systems with time-delayed protocols -- Robust output containment control of multi-agent systems with unknown heterogeneous nonlinear uncertainties in directed networks -- Distributed event-based consensus control of multi-agent system with matching nonlinear uncertainties.
Contained By:	Springer Nature eBook
Subject:	Multiagent systems. -
Online resource:	https://doi.org/10.1007/978-981-96-0950-5
ISBN:	9789819609505

Distributed cooperative control and optimization for multi-agent systems
Wang, Qing.

Distributed cooperative control and optimization for multi-agent systems[electronic resource] /by Qing Wang, Bin Xin, Jie Chen. - Singapore :Springer Nature Singapore :2025. - ix, 149 p. :ill. (chiefly color), digital ;24 cm.

Introduction -- Disturbance observer-based sliding mode control for multi-agent systems with mismatched uncertainties -- Observer-based containment for a class of nonlinear multi-agent systems with time-delayed protocols -- Robust output containment control of multi-agent systems with unknown heterogeneous nonlinear uncertainties in directed networks -- Distributed event-based consensus control of multi-agent system with matching nonlinear uncertainties.

This book provides a concise and in-depth exposition of distributed control and optimization problems of multi-agent systems. The book integrates various ideas and tools from dynamic systems, control theory, graph theory, and optimization to address the special challenges posed by such complexities in the environment as communication delay, topological dynamics, and environmental uncertainties. In order to deal with the mismatched uncertainties and time delay, observer-based controller and sliding mode control are developed to achieve consensus control. When there is a leader or multiple leaders in the communication topologies, containment control is required. The book studies both state and output containment for nonlinear multi-agent systems with undirected or directed networks. Furthermore, event-triggered schemes are proposed to reduce communication and computation costs. Distributed optimization for multi-agent systems is an interesting topic that has attracted more and more attention due to its wide range of applications such as smart grids, sensor networks, and mobile manipulators. In distributed optimization, the goal is to optimize the global cost function, which is the sum of all local cost functions, each of which is known only by its own local agent. Distributed nonsmooth convex optimization for multi-agent systems based on proximal operators is developed to achieve distributed optimal consensus.

ISBN: 9789819609505

Standard No.: 10.1007/978-981-96-0950-5doiSubjects--Topical Terms:

1048048
Multiagent systems.

LC Class. No.: TJ215.5

Dewey Class. No.: 006.30285436

Distributed cooperative control and optimization for multi-agent systems
LDR:02932nmm a2200325 a 4500 001 2409269
003 DE-He213
005 20250302115236.0
006 m d
007 cr nn 008maaau
008 260204s2025 si s 0 eng d
020 $a 9789819609505 $q (electronic bk.)
020 $a 9789819609499 $q (paper)
024 7 $a 10.1007/978-981-96-0950-5 $2 doi
035 $a 978-981-96-0950-5
040 $a GP $c GP
041 0 $a eng
050 4 $a TJ215.5
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
072 7 $a TJFM $2 thema
082 0 4 $a 006.30285436 $2 23
090 $a TJ215.5 $b .W246 2025
100 1 $a Wang, Qing. $3 898346
245 1 0 $a Distributed cooperative control and optimization for multi-agent systems $h [electronic resource] / $c by Qing Wang, Bin Xin, Jie Chen.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2025.
300 $a ix, 149 p. : $b ill. (chiefly color), digital ; $c 24 cm.
505 0 $a Introduction -- Disturbance observer-based sliding mode control for multi-agent systems with mismatched uncertainties -- Observer-based containment for a class of nonlinear multi-agent systems with time-delayed protocols -- Robust output containment control of multi-agent systems with unknown heterogeneous nonlinear uncertainties in directed networks -- Distributed event-based consensus control of multi-agent system with matching nonlinear uncertainties.
520 $a This book provides a concise and in-depth exposition of distributed control and optimization problems of multi-agent systems. The book integrates various ideas and tools from dynamic systems, control theory, graph theory, and optimization to address the special challenges posed by such complexities in the environment as communication delay, topological dynamics, and environmental uncertainties. In order to deal with the mismatched uncertainties and time delay, observer-based controller and sliding mode control are developed to achieve consensus control. When there is a leader or multiple leaders in the communication topologies, containment control is required. The book studies both state and output containment for nonlinear multi-agent systems with undirected or directed networks. Furthermore, event-triggered schemes are proposed to reduce communication and computation costs. Distributed optimization for multi-agent systems is an interesting topic that has attracted more and more attention due to its wide range of applications such as smart grids, sensor networks, and mobile manipulators. In distributed optimization, the goal is to optimize the global cost function, which is the sum of all local cost functions, each of which is known only by its own local agent. Distributed nonsmooth convex optimization for multi-agent systems based on proximal operators is developed to achieve distributed optimal consensus.
650 0 $a Multiagent systems. $3 1048048
650 1 4 $a Automation. $3 633305
650 2 4 $a Control and Systems Theory. $3 3381515
700 1 $a Xin, Bin. $3 3512766
700 1 $a Chen, Jie. $3 623762
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-96-0950-5
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)