Title
Neural-Network-Based Distributed Adaptive Robust Control for a Class of Nonlinear Multiagent Systems With Time Delays and External Noises.
Abstract
A class of nonlinear multiagent systems with time delays and external noises is investigated, and a distributed adaptive robust control protocol is developed. It is the first time for a class of multiagent systems to take both time delays and external noises into consideration. By virtue of Lyapunov-Krasovskii functional and Young's inequality, the effects of time delay can be eliminated. Then, to exclude external noises, a robustifying term is introduced to eliminate the negative effects of these noises. Moreover, neural networks are utilized to learn the unknown nonlinear terms to adapt to the complex external environment. Finally, a numerical simulation is conducted to validate the effectiveness of our distributed control protocol.
Year
DOI
Venue
2016
10.1109/TSMC.2015.2470635
IEEE Trans. Systems, Man, and Cybernetics: Systems
Keywords
Field
DocType
Multi-agent systems,Delay effects,Noise,Protocols,Artificial neural networks,Robust control,Robustness
Nonlinear system,Computer simulation,Control theory,Computer science,Robustness (computer science),Multi-agent system,Artificial intelligence,Artificial neural network,Robust control,Machine learning
Journal
Volume
Issue
ISSN
46
6
2168-2216
Citations 
PageRank 
References 
16
0.53
28
Authors
6
Name
Order
Citations
PageRank
Hong-Wen Ma11609.16
Zhuo Wang2172.91
Ding Wang3187068.16
Derong Liu45457286.88
Pengfei Yan51484.82
Qinglai Wei62494110.44