Paper Info
Title
Asymptotic Tracking Control for Uncertain MIMO Systems: A Biologically Inspired ESN Approach
Abstract
In this study, a biologically inspired echo state network (ESN)-based method is established for the asymptotic tracking control of a class of uncertain multi-input multi-output (MIMO) systems. By mimicking the characters of real biological systems, a diversified multiclustered echo state network (DMCESN) is proposed in this work and then it is applied to deal with the modeling uncertainties and co...
Year
DOI
Venue
2022
10.1109/TNNLS.2021.3091641
IEEE Transactions on Neural Networks and Learning Systems
Keywords
DocType
Volume
Artificial neural networks,Reservoirs,Neurons,MIMO communication,Control systems,Uncertainty,Robots
Journal
33
Issue
ISSN
Citations 
5
2162-237X
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Qing Chen100.34
Kai Zhao210413.74
Xiumin Li302.03
Yujuan Wang424611.57