Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/644984
Title: Backstepping approach to a class of hierarchical multi-agent systems with communication disturbance
Authors: Wenjun Xiong;Daniel W.C. Ho;Jinde Cao;Wei Xing Zheng
subject: hierarchical structure|hierarchical multiagent systems|nonlinear function approximation|mathematical models|HMS|external noise|communication disturbance|radial basis function neural networks|backstepping approach
Year: 2016
Publisher: IEEE
Abstract: In this study, mathematical models of hierarchical multi-agent systems (HMSs) are first proposed to demonstrate the hierarchical structure of multi-agent systems. Communication disturbance is also considered in HMSs since disturbance often appears when information is transmitted among agents due to various uncertainties such as model unsteadiness and external noise. Radial basis function neural networks are applied to approximate the non-linear functions of the communication disturbance. Then, by applying a backstepping method based on the hierarchical structure of HMSs, a simple condition is derived to ensure the stability of HMSs with disturbance.
URI: http://localhost/handle/Hannan/177427
http://localhost/handle/Hannan/644984
ISSN: 1751-8644
1751-8652
volume: 10
issue: 9
Appears in Collections:2016

Files in This Item:
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Title: Backstepping approach to a class of hierarchical multi-agent systems with communication disturbance
Authors: Wenjun Xiong;Daniel W.C. Ho;Jinde Cao;Wei Xing Zheng
subject: hierarchical structure|hierarchical multiagent systems|nonlinear function approximation|mathematical models|HMS|external noise|communication disturbance|radial basis function neural networks|backstepping approach
Year: 2016
Publisher: IEEE
Abstract: In this study, mathematical models of hierarchical multi-agent systems (HMSs) are first proposed to demonstrate the hierarchical structure of multi-agent systems. Communication disturbance is also considered in HMSs since disturbance often appears when information is transmitted among agents due to various uncertainties such as model unsteadiness and external noise. Radial basis function neural networks are applied to approximate the non-linear functions of the communication disturbance. Then, by applying a backstepping method based on the hierarchical structure of HMSs, a simple condition is derived to ensure the stability of HMSs with disturbance.
URI: http://localhost/handle/Hannan/177427
http://localhost/handle/Hannan/644984
ISSN: 1751-8644
1751-8652
volume: 10
issue: 9
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7470974.pdf443.59 kBAdobe PDFThumbnail
Preview File
Title: Backstepping approach to a class of hierarchical multi-agent systems with communication disturbance
Authors: Wenjun Xiong;Daniel W.C. Ho;Jinde Cao;Wei Xing Zheng
subject: hierarchical structure|hierarchical multiagent systems|nonlinear function approximation|mathematical models|HMS|external noise|communication disturbance|radial basis function neural networks|backstepping approach
Year: 2016
Publisher: IEEE
Abstract: In this study, mathematical models of hierarchical multi-agent systems (HMSs) are first proposed to demonstrate the hierarchical structure of multi-agent systems. Communication disturbance is also considered in HMSs since disturbance often appears when information is transmitted among agents due to various uncertainties such as model unsteadiness and external noise. Radial basis function neural networks are applied to approximate the non-linear functions of the communication disturbance. Then, by applying a backstepping method based on the hierarchical structure of HMSs, a simple condition is derived to ensure the stability of HMSs with disturbance.
URI: http://localhost/handle/Hannan/177427
http://localhost/handle/Hannan/644984
ISSN: 1751-8644
1751-8652
volume: 10
issue: 9
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7470974.pdf443.59 kBAdobe PDFThumbnail
Preview File