多智能体系分布式协同控制-英文版 虞文武 温广辉 陈关荣 曹进德 高等教育出版社【.正版】 pdf pdb 阿里云 极速 mobi caj kindle 下载

由于多智能体系统的广泛应用，其分布式协同控制成为数学、物理、生物、工程、管理等众多相关领域的一个热点研究方向，相互合作的分布式协议成为多智能体网络系统实现协同控制至关重要的因素。

《多智能体系统分布式协同控制（英文版）/网络科学与工程丛书》详细介绍了多智能体系统的研究背景和相关研究进展，深入探讨了完全基于分布式信息的多智能体系统控制协议设计，研究了多智能体传感网络的滤波器设计等关键问题。全书从理论到应用系统地研究了多智能体系统协同控制的研究进展，对于有基础的研究者和感兴趣的初学者，都具有非常高的参考价值。

1 Introduction

1．1 Background

1．1．1 Networked Multi-agent Systems

1．1．2 Collective Behaviors and Cooperative Control iMulti-agent Systems

1．1．3 Network Control iMulti-agent Systems

1．1．4 Distributed Consensus Filtering iSensor Networks

1．2 Organization

2 Consensus iMulti-agent Systems

2．1 Consensus iLinear Multi-agent Systems

2．1．1 Preliminaries

2．1．2 Model Formulatioand Results

2．2 Consensus iNonlinear Multi-agent Systems

2．2．1 Preliminaries and Model Formulation

2．2．2 Local Consensus of Multi-agent Systems

2．2．3 Global Consensus of Multi-agent Systems iGeneral Networks

2．2．4 Global Consensus of Multi-agent Systems iVirtual Networks

2．2．5 SimulatioExamples

2．3 Notes

3 Second-Order Consensus iMulti-agent Systems

3．1 Second-Order Consensus iLinear Multi-agent Systems

3．1．1 Model Formulation

3．1．2 Second-Order Consensus iDirected Networks

3．1．3 Second-Order Consensus iDelayed Directed Networks

3．1．4 SimulatioExamples

3．2 Second-Order Consensus iNonlinear Multi-agent Systems

3．2．1 Preliminaries

3．2．2 Second-Order Consensus iStrongly Connected Networks

3．2．3 Second-Order Consensus iRooted Networks

3．2．4 SimulatioExamples

3．3 Notes

4 Higher-Order Consensus iMulti-agent Systems

4．1 Preliminaries

4．2 Higher-Order Consensus ia General Form

4．2．1 SynchronizatioiComplex Networks

4．2．2 Higher-Order Consensus ia General Form

4．2．3 Consensus RegioiHigher-Order Consensus

4．3 Leader-Follower Control iMulti-agent Systems

4．3．1 Leader-Follower Control iMulti-agent Systems with Full-State Feedback

4．3．2 Leader-Follower Control with Observers

4．4 SimulatioExamples

4．4．1 Consensus Regions

4．4．2 Leader-Follower Control with Full-State Feedback

4．4．3 Leader-Follower Control with Observers

4．5 Notes

5 Stability Analysis of Swarming Behaviors

5．1 Preliminaries

5．2 Analysis of Swarm Cohesion

5．3 Swarm Cohesioia Noisy Environment

5．4 CohesioiSwarms with Switched Topologies

5．5 CohesioiSwarms with Changing Topologies

5．6 SimulatioExamples

5．7 Notes

6 Distributed Leader-Follower Flocking Control

6．1 Preliminaries

6．1．1 Model Formulation

6．1．2 Nonsmooth Analysis

6．2 Distributed Leader-Follower Control with Pinning Observers

6．3 SimulatioExamples

6．4 Notes

7 Consensus of Multi-agent Systems with Sampled Data Information

7．1 Problem Statement

7．2 Second-Order Consensus of Multi-agent Systems with Sampled Full Information

7．2．1 Second-Order Consensus of Multi-agent Systems with Sampled Full Information

7．2．2 Selectioof Sampling Periods

7．2．3 Desigof Coupling Gains

7．2．4 Consensus Regiofor the Network Spectrum

7．2．5 Second-Order Consensus iDelayed Undirected Networks with Sampled Positioand Velocity Data

7．2．6 SimulatioExamples

7．3 Second-Order Consensus of Multi-agent Systems with Sampled PositioInformation

7．3．1 Second-Order Consensus iMulti-agent Dynamical Systems with Sampled PositioData

7．3．2 SimulatioExamples

7．4 Consensus of Multi-agent Systems with Nonlinear Dynamics and Sampled Information

7．4．1 The Case with a Fixed and Strongly Connected Topology

7．4．2 The Case with Topology Containing a Directed Spanning Tree

7．4．3 The Case with Topology Having no Directed Spanning Tree

7．5 Notes

8 Consensus of Second-Order Multi-agent Systems with

Intermittent Communication

8．1 Problem Statement

8．2 The Case with a Strongly Connected Topology

8．3 The Case with a Topology Having a Directed Spanning Tree

8．4 Consensus of Second-Order Multi-agent Systems with Nonlinear Dynamics and Intermittent Communication

8．5 Notes

9 Distributed Adaptive Control of Multi-agent Systems

9．1 Distributed Adaptive Control iComplex Networks

9．1．1 Preliminaries

9．1．2 Distributed Adaptive Control iComplex Networks

9．1．3 Pinning Edges Control

9．1．4 SimulatioExamples

9．2 Distributed Control Gains Desigfor Second-Order Consensus iNonlinear Multi-agent Systems

9． 2．1 Preliminaries

9．2．2 Distributed Control Gains Design： Leaderless Case

9．2．3 Distributed Control Gains Design： Leader-Follower Case

9．2．4 SimulatioExamples

9．3 Notes

10 Distributed Consensus Filtering iSensor Networks

10．1 Preliminaries

10．2 Distributed Consensus Filters Desigfor Sensor Networks with Fully-Pinned Controllers

10．3 Distributed Consensus Filters Desigfor Sensor Networks with Pinning Controllers

10．4 Distributed Consensus Filters Desigfor Sensor Networks with Pinning Observers

10．5 SimulatioExamples

10．6 Notes

11 Delay-Induced Consensus and Quasi-Consensus iMulti-agent Systems

11．1 Problem Statement

11．2 Delay-Induced Consensus and Quasi-Consensus iMulti-agent Dynamical Systems

11．3 Motivatiofor Quasi-Consensus Analysis

11．4 SimulatioExamples

11．5 Notes

12 Conclusions and Future Work

12．1 Conclusions

12．2 Future Work

Bibliography

Index

虞文武，东南大学教授、博士生导师、复杂系 统与网络科学研究中心副主任、复杂系统协同 控制实验室主任。于2004年和2007年分别获 得东南大学学士和硕士学位，2010年获得香港 城市大学电子工程系博士学位。现主要从事复 杂网络系统协同分析、控制与优化等相关研究，主持参与基金项目10多项。入选国家“万人计划”青年拔尖人才；2014-2016年人选ThomsoReuters全球高被引科学家，SCI H指数 为35，25篇ESI高被引论文（学科前1%）；曾获2010年江苏 省科学技术奖一等奖、201 5年北京市科学技术奖二等奖、江苏 省数学成就奖、Scopus“青年科学之星”信息科学领域金奖、国内外学术会议和机构论文奖6篇等。合作出版图书1种、专著1种，发表SCI论文90余篇。

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