Cooperative control of multi-agent systems a scale-free protocol design /

This monograph represents the outcome of research effort of the authors on scalable synchronization of large-scale multi-agent systems (MAS). Cooperative control of multi-agent systems has been growing in popularity and is highly interdisciplinary in recent years. The application of synchronization...

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Main Author: Liu, Zhenwei,
Other Authors: Nojavanzadeh, Donya,, Saberi, Ali, 1949-, SpringerLink (Online service)
Format: eBook
Language: English
Published: Cham : Springer, [2023]
Physical Description: 1 online resource (xiii, 392 pages) : ilustrations (chiefly color).
Series: Studies in systems, decision and control ; v. 248.
Subjects:
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100 1 |a Liu, Zhenwei,  |e author. 
245 1 0 |a Cooperative control of multi-agent systems :  |b a scale-free protocol design /  |c Zhenwei Liu, Donya Nojavanzadeh, Ali Saberi. 
264 1 |a Cham :  |b Springer,  |c [2023] 
264 4 |c ©2023. 
300 |a 1 online resource (xiii, 392 pages) :  |b ilustrations (chiefly color). 
336 |a text  |b txt  |2 rdacontent. 
337 |a computer  |b c  |2 rdamedia. 
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490 1 |a Studies in systems, decision and control ;  |v volume 248. 
504 |a Includes bibliographical references. 
520 |a This monograph represents the outcome of research effort of the authors on scalable synchronization of large-scale multi-agent systems (MAS). Cooperative control of multi-agent systems has been growing in popularity and is highly interdisciplinary in recent years. The application of synchronization of MAS includes automobile systems, aerospace systems, multiple-satellite GPS, high-resolution satellite imagery, aircraft formations, highway traffic platooning, industrial process control with multiple processes, and more. Most of the proposed protocols in the literature for synchronization of MAS require some knowledge of the communication network such as bounds on the spectrum of the associated Laplacian matrix and the number of agents. These protocols suffer from scale fragility wherein stability properties are lost for large-scale networks or when the communication graph changes. In the past few years, the authors of this monograph have worked on developing scale-free protocol design for various cases of MAS problems. The key contribution of the monograph is to offer a scale-free design framework and provide scale-free protocols to achieve synchronization, delayed synchronization, and almost synchronization in the presence of input and communication delays, input saturation and external disturbances. The scale-free design framework solely is based on the knowledge of agent models and does not depend on information about the communication network such as the spectrum of the associated Laplacian matrix or size of the network. Drawing upon their extensive work in this area, the authors provide a thorough treatment of agents with higher-order dynamics, different classes of models for agents, and the underlying networks representing actions of the agents. The high technical level of their presentation and their rigorous mathematical approach make this monograph a timely and valuable resource that will fill a gap in the existing literature. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed December 15, 2022). 
505 0 |a Intro -- Acknowledgements -- Contents -- 1 Introduction -- 1.1 Cooperative Control of Multi-agent Systems -- 1.2 Outline -- 2 Notations and Preliminaries -- 2.1 Linear Algebra -- 2.2 Signal and System Norms -- 2.3 Graphs -- 2.4 Multi-agent Systems and Graphs -- 2.5 Passivity -- 2.5.1 Continuous-Time System -- 2.5.2 Discrete-Time System -- 3 Synchronization of Continuous-Time MAS -- 3.1 Problem Formulation -- 3.2 Scalable Output Synchronization -- 3.2.1 Architecture of the Protocol -- 3.2.2 Protocol Design -- 3.2.3 Special Case: Homogeneous MAS -- 3.3 Scalable Regulated Output Synchronization. 
505 8 |a 3.3.1 Architecture of the Protocol -- 3.3.2 Protocol Design -- 3.4 Numerical Examples -- 4 Synchronization of Discrete-Time MAS -- 4.1 Homogeneous MAS with Non-introspective Agents -- 4.1.1 Problem Formulation -- 4.1.2 Scalable State Synchronization -- 4.2 Heterogeneous MAS with Introspective Agents -- 4.2.1 Scalable Output Synchronization -- 4.2.2 Scalable Regulated Output Synchronization -- 4.3 Numerical Examples -- 5 Regulated State Synchronization of Homogeneous MAS in the Presence of Input Delays -- 5.1 Problem Formulation -- 5.2 Scalable Regulated State Synchronization. 
505 8 |a 5.2.1 Solvability Conditions -- 5.2.2 Protocol Design -- 5.2.3 Special Case: MAS with Full-State Coupling -- 5.3 Numerical Examples -- 5.3.1 Example 1: Continuous-Time MAS -- 5.3.2 Example 2: Discrete-Time MAS -- 6 State Synchronization of Homogeneous Continuous-Time MAS in the Presence of Nonuniform Communication Delays -- 6.1 Problem Formulation -- 6.2 Scalable State Synchronization -- 6.2.1 Solvability Condition and Protocol Design for Arbitrary Constant Reference Trajectory y Subscript r Baseline element of double struck upper R Superscript pyrinmathbbRp. 
505 8 |a 6.2.2 Necessary and Sufficient Solvability Conditions and Protocol Design -- 6.3 Numerical Examples -- 7 State Synchronization of Homogeneous Discrete-Time MAS in the Presence of Nonuniform Communication Delays -- 7.1 Problem Formulation -- 7.2 Scalable State Synchronization -- 7.3 Numerical Examples -- 8 Regulated Output Synchronization of Heterogeneous MAS in the Presence of Nonuniform Communication Delays -- 8.1 Problem Formulation -- 8.2 Scalable Regulated Output Synchronization -- 8.2.1 Architecture of the Protocol -- 8.2.2 Protocol Design -- 8.3 Numerical Examples. 
505 8 |a 8.3.1 Continuous-Time MAS -- 8.3.2 Discrete-Time MAS -- 9 Delayed Regulated Synchronization of Continuous-Time MAS in the Presence of Unknown, Non-uniform, and Arbitrarily Large Communication Delays -- 9.1 Homogeneous MAS with Non-introspective Agents -- 9.1.1 Problem Formulation -- 9.1.2 Scalable Delayed Regulated State Synchronization -- 9.2 Heterogeneous MAS with Introspective Agents -- 9.2.1 Problem Formulation -- 9.2.2 Scalable Delayed Regulated Output Synchronization -- 9.3 Numerical Examples -- 9.3.1 Example 1. Homogeneous MAS -- 9.3.2 Example 2. Heterogeneous MAS. 
650 0 |a Multiagent systems. 
650 0 |a Automatic control. 
650 6 |a Systèmes multiagents (Intelligence artificielle) 
650 6 |a Commande automatique. 
650 7 |a Automatic control.  |2 fast. 
650 7 |a Multiagent systems.  |2 fast. 
700 1 |a Nojavanzadeh, Donya,  |e author. 
700 1 |a Saberi, Ali,  |d 1949-  |1 https://id.oclc.org/worldcat/entity/E39PCjy7TDhcKTfggvYyHwhwP3,  |e author. 
710 2 |a SpringerLink (Online service) 
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830 0 |a Studies in systems, decision and control ;  |v v. 248. 
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