典型文献
Adaptive Control of Discrete-time Nonlinear Systems Using ITF-ORVFL
文献摘要：
Random vector functional ink (RVFL) networks belong to a class of single hidden layer neural networks in which some parameters are randomly selected. Their network structure in which contains the direct links between inputs and outputs is unique, and stability analysis and real-time performance are two difficulties of the control systems based on neural networks. In this paper, combining the advantages of RVFL and the ideas of online sequential extreme learning machine (OS-ELM) and initial-training-free online extreme learning machine (ITF-OELM), a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm (ITF-ORVFL) is investigated for training RVFL. The link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed, and the stability for nonlinear systems based on this learning algorithm is analyzed. The experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.
文献关键词：
中图分类号：
作者姓名：
Xiaofei Zhang;Hongbin Ma;Wenchao Zuo;Man Luo
作者机构：
School of Automation,Beijing Institute of Technology,Beijing 100081;School of Vehicle and Mobility,Tsinghua University,Beijing 100084,China;School of Automation,Beijing Institute of Technology,and also with the State Key Laboratory of Intelligent Control and Decision of Complex Systems(Beijing Institute of Technology),Beijing 100081;Beijing Institute of Electronic System Engineering,Beijing 100854,China;School of Automation,Beijing Institute of Technology,Beijing 100081,and she is with Ant Group,Beijing 310013,China
文献出处：
引用格式：
[1]Xiaofei Zhang;Hongbin Ma;Wenchao Zuo;Man Luo-.Adaptive Control of Discrete-time Nonlinear Systems Using ITF-ORVFL)[J].自动化学报（英文版）,2022(03):556-563
A类：
ORVFL,OELM
B类：
Adaptive,Control,Discrete,Nonlinear,Systems,Using,ITF,Random,vector,functional,networks,belong,class,single,hidden,layer,neural,which,some,parameters,are,randomly,selected,Their,structure,contains,direct,links,between,inputs,outputs,unique,stability,analysis,real,performance,difficulties,control,systems,In,this,paper,combining,advantages,ideas,extreme,learning,machine,OS,initial,training,free,novel,algorithm,named,investigated,can,analytically,determined,sequentially,arriving,data,by,high,speed,nonlinear,analyzed,experiment,results,indicate,that,proposed,effective,coping,nonparametric,uncertainty
AB值：
0.472523
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