000			03799nam a2200349za04500
001			17157
008			050703s2011 xxk eng d
020			_a9780857291691 99780857291691
082			_a629.8 _b223
100			_aRen, Wei. _eauthor. _934517
245			_aDistributed Coordination of Multi-agent Networks _h[electronic resource]: _bEmergent Problems, Models, and Issues / _cby Wei Ren, Yongcan Cao.
300			_aXVIII, 310 p. _bonline resource.
490			_aCommunications and Control Engineering
490			_x-0178-5354
505			_aPart I: Preliminaries and Literature Review -- Preliminaries -- Overview of Recent Research in Distributed Multi-agent Coordination -- Part II: Emergent Problems in Distributed Multi-agent Coordination -- Collective Periodic Motion Coordination -- Collective Tracking with a Dynamic Leader -- Containment Control with Multiple Leaders -- Part III: Emergent Models in Distributed Multi-agent Coordination -- Networked Lagrangian Systems -- Networked Fractional-order Systems -- Part IV Emergent Issues in Distributed Multi-agent Coordination -- Sampled-data Setting -- Optimality Aspect -- Time Delay.
520			_aMulti-agent systems have numerous civilian, homeland security, and military applications; however, for all these applications, communication bandwidth, sensing range, power constraints, and stealth requirements preclude centralized command and control. The alternative is distributed coordination, which is more promising in terms of scalability, robustness, and flexibility.Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders.The authors' models for distributed coordination arise from physical constraints and the complex environments in which multi-agent systems operate; they include Lagrangian models - more realistic for mechanical-systems modeling than point models - and fractional-order systems which better represent the consequences of environmental complexity.Other issues addressed in the text include the time delays inherent in networked systems, optimality concerns associated with the deisgn of energy-efficent algorithms, and the use of sampled-data settings in systems with intermittent neightbor-neighbor contact. Researchers, graduate students, and engineers interested in the field of multi-agent systems will find this monograph useful in introducing them to presently emerging research directions and problems in distributed coordination of multi-agent networks.
650			_aEngineering. _996
650			_aArtificial intelligence. _933648
650			_aEngineering. _996
650			_aControl. _924383
650			_aArtificial Intelligence (incl. Robotics). _923200
650			_933854 _aROBOTICS AND AUROMATION
650			_933627 _aCOMMUNICATIONS ENGINEERING, NETWORKS
650			_933972 _aSYSTEMS THEORY
650			_933972 _aSYSTEMS THEORY
650			_930656 _aTELECOMUNICACIÓN
700			_aCao, Yongcan. _933855
700			_eauthor. _934519
710			_aSpringerLink (Online service) _9111
856			_uhttp://springer.escuelaing.metaproxy.org/book/10.1007/978-0-85729-169-1 _yir a documento _qURL
942			_2ddc _cCF
999			_c13903 _d13903