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The Resource Iterative learning control for multi-agent systems coordination, by Shiping Yang, Jian-Xin Xu, Xuefang Li, Dong Shen
Iterative learning control for multi-agent systems coordination, by Shiping Yang, Jian-Xin Xu, Xuefang Li, Dong Shen
Resource Information
The item Iterative learning control for multi-agent systems coordination, by Shiping Yang, Jian-Xin Xu, Xuefang Li, Dong Shen represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Iterative learning control for multi-agent systems coordination, by Shiping Yang, Jian-Xin Xu, Xuefang Li, Dong Shen represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
- Summary
- "This book gives a comprehensive overview of the intersection between ILC and MAS, the range of topics include basic to advanced theories, rigorous mathematics to engineering practice, and linear to nonlinear systems. It addresses the crucial multi-agent coordination and control challenges that can be solved by ILC methods. Through systematic discussion of network theory and intelligent control, the authors explore future research possibilities, develop new tools, and provide numerous applications such as the power grid, communication and sensor networks, intelligent transportation system, and formation control. Readers will gain a roadmap to the latest advances in the fields and use their newfound knowledge to design their own algorithms"--
- Language
- eng
- Extent
- 1 online resource.
- Note
- Made available via IEEE Xplore Digital Library
- Contents
-
- Optimal Iterative Learning Control for Multi-agent Consensus Tracking
- Iterative Learning Control for Multi-agent Coordination Under Iteration-Varying Graph
- Iterative Learning Control for Multi-agent Coordination with Initial State Error
- Multi-agent Consensus Tracking with Input Sharing by Iterative Learning Control
- A HOIM-Based Iterative Learning Control Scheme for Multi-agent Formation
- P-type Iterative Learning for Non-parameterized Systems with Uncertain Local Lipschitz Terms
- Synchronization for Nonlinear Multi-agent Systems by Adaptive Iterative Learning Control
- Distributed Adaptive Iterative Learning Control for Nonlinear Multi-agent Systems with State Constraints
- Synchronization for Networked Lagrangian Systems under Directed Graphs
- Generalized Iterative Learning for Economic Dispatch Problem in a Smart Grid
- Summary and Future Research Directions
- Appendix A: Graph Theory Revisit
- Appendix B: Detailed Proofs
- Isbn
- 9781119189077
- Label
- Iterative learning control for multi-agent systems coordination
- Title
- Iterative learning control for multi-agent systems coordination
- Statement of responsibility
- by Shiping Yang, Jian-Xin Xu, Xuefang Li, Dong Shen
- Subject
-
- Iterative methods (Mathematics)
- Iterative methods (Mathematics)
- Iterative methods (Mathematics)
- Iterative methods (Mathematics)
- Machine learning
- Machine learning
- Machine learning
- Machine learning
- Multiagent systems
- Multiagent systems
- Electronic resources
- Multiagent systems
- Multiagent systems
- Intelligent control systems
- Intelligent control systems
- Intelligent control systems
- Intelligent control systems
- Language
- eng
- Summary
- "This book gives a comprehensive overview of the intersection between ILC and MAS, the range of topics include basic to advanced theories, rigorous mathematics to engineering practice, and linear to nonlinear systems. It addresses the crucial multi-agent coordination and control challenges that can be solved by ILC methods. Through systematic discussion of network theory and intelligent control, the authors explore future research possibilities, develop new tools, and provide numerous applications such as the power grid, communication and sensor networks, intelligent transportation system, and formation control. Readers will gain a roadmap to the latest advances in the fields and use their newfound knowledge to design their own algorithms"--
- Assigning source
- Provided by publisher
- Cataloging source
- DLC
- http://library.link/vocab/creatorDate
- 1987-
- http://library.link/vocab/creatorName
- Yang, Shiping
- Index
- index present
- LC call number
- TJ217.5
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- http://library.link/vocab/relatedWorkOrContributorDate
-
- 1985-
- 1982-
- http://library.link/vocab/relatedWorkOrContributorName
-
- Xu, Jian-Xin
- Li, Xuefang
- Shen, Dong
- IEEE Xplore
- John Wiley & Sons
- Institute of Electrical and Electronics Engineers
- http://library.link/vocab/subjectName
-
- Intelligent control systems
- Multiagent systems
- Machine learning
- Iterative methods (Mathematics)
- Intelligent control systems
- Iterative methods (Mathematics)
- Machine learning
- Multiagent systems
- Label
- Iterative learning control for multi-agent systems coordination, by Shiping Yang, Jian-Xin Xu, Xuefang Li, Dong Shen
- Note
- Made available via IEEE Xplore Digital Library
- Bibliography note
- Includes bibliographical references (pages 233-243) and index
- Carrier category
- online resource
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Optimal Iterative Learning Control for Multi-agent Consensus Tracking -- Iterative Learning Control for Multi-agent Coordination Under Iteration-Varying Graph -- Iterative Learning Control for Multi-agent Coordination with Initial State Error -- Multi-agent Consensus Tracking with Input Sharing by Iterative Learning Control -- A HOIM-Based Iterative Learning Control Scheme for Multi-agent Formation -- P-type Iterative Learning for Non-parameterized Systems with Uncertain Local Lipschitz Terms -- Synchronization for Nonlinear Multi-agent Systems by Adaptive Iterative Learning Control -- Distributed Adaptive Iterative Learning Control for Nonlinear Multi-agent Systems with State Constraints -- Synchronization for Networked Lagrangian Systems under Directed Graphs -- Generalized Iterative Learning for Economic Dispatch Problem in a Smart Grid -- Summary and Future Research Directions -- Appendix A: Graph Theory Revisit -- Appendix B: Detailed Proofs
- Extent
- 1 online resource.
- Form of item
- online
- Isbn
- 9781119189077
- Isbn Type
- (epub)
- Lccn
- 2016056133
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- n
- Specific material designation
- remote
- System control number
-
- (OCoLC)965446716
- (OCoLC)ocn965446716
- Label
- Iterative learning control for multi-agent systems coordination, by Shiping Yang, Jian-Xin Xu, Xuefang Li, Dong Shen
- Note
- Made available via IEEE Xplore Digital Library
- Bibliography note
- Includes bibliographical references (pages 233-243) and index
- Carrier category
- online resource
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Optimal Iterative Learning Control for Multi-agent Consensus Tracking -- Iterative Learning Control for Multi-agent Coordination Under Iteration-Varying Graph -- Iterative Learning Control for Multi-agent Coordination with Initial State Error -- Multi-agent Consensus Tracking with Input Sharing by Iterative Learning Control -- A HOIM-Based Iterative Learning Control Scheme for Multi-agent Formation -- P-type Iterative Learning for Non-parameterized Systems with Uncertain Local Lipschitz Terms -- Synchronization for Nonlinear Multi-agent Systems by Adaptive Iterative Learning Control -- Distributed Adaptive Iterative Learning Control for Nonlinear Multi-agent Systems with State Constraints -- Synchronization for Networked Lagrangian Systems under Directed Graphs -- Generalized Iterative Learning for Economic Dispatch Problem in a Smart Grid -- Summary and Future Research Directions -- Appendix A: Graph Theory Revisit -- Appendix B: Detailed Proofs
- Extent
- 1 online resource.
- Form of item
- online
- Isbn
- 9781119189077
- Isbn Type
- (epub)
- Lccn
- 2016056133
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- n
- Specific material designation
- remote
- System control number
-
- (OCoLC)965446716
- (OCoLC)ocn965446716
Subject
- Iterative methods (Mathematics)
- Iterative methods (Mathematics)
- Iterative methods (Mathematics)
- Iterative methods (Mathematics)
- Machine learning
- Machine learning
- Machine learning
- Machine learning
- Multiagent systems
- Multiagent systems
- Electronic resources
- Multiagent systems
- Multiagent systems
- Intelligent control systems
- Intelligent control systems
- Intelligent control systems
- Intelligent control systems
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