000 04277nam a22005175i 4500
001 978-0-85729-169-1
003 DE-He213
005 20140220083712.0
007 cr nn 008mamaa
008 101130s2011 xxk| s |||| 0|eng d
020 _a9780857291691
_9978-0-85729-169-1
024 7 _a10.1007/978-0-85729-169-1
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aRen, Wei.
_eauthor.
245 1 0 _aDistributed Coordination of Multi-agent Networks
_h[electronic resource] :
_bEmergent Problems, Models, and Issues /
_cby Wei Ren, Yongcan Cao.
264 1 _aLondon :
_bSpringer London,
_c2011.
300 _aXVIII, 310 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aCommunications and Control Engineering,
_x0178-5354
505 0 _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 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aSystems theory.
650 0 _aTelecommunication.
650 1 4 _aEngineering.
650 2 4 _aControl.
650 2 4 _aSystems Theory, Control.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aRobotics and Automation.
650 2 4 _aCommunications Engineering, Networks.
700 1 _aCao, Yongcan.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780857291684
830 0 _aCommunications and Control Engineering,
_x0178-5354
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-85729-169-1
912 _aZDB-2-ENG
999 _c105148
_d105148