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Iterative learning control for multi-agent systems coordination

A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, this book showcases recent advances and industrially relevant applications. Readers are first given a comprehensive overview of the intersection between ILC and MAS, then introduced to a ran...

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Detalles Bibliográficos
Autores principales: Yang, Shiping, Xu, Jian-Xin, Li, Xuefang, Shen, Dong
Lenguaje:eng
Publicado: Wiley-IEEE Press 2016
Materias:
Acceso en línea:http://cds.cern.ch/record/2259084
Descripción
Sumario:A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, this book showcases recent advances and industrially relevant applications. Readers are first given a comprehensive overview of the intersection between ILC and MAS, then introduced to a range of topics that include both basic and advanced theoretical discussions, rigorous mathematics, engineering practice, and both linear and nonlinear systems. Through systematic discussion of network theory and intelligent control, the authors explore future research possibilities, develop new tools, and provide numerous applications such as power grids, communication and sensor networks, intelligent transportation systems, and formation control. Readers will gain a roadmap of the latest advances in the fields and can use their newfound knowledge to design their own algorithms.