Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network

Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network

In order to improve the identification accuracy of dynamic system, multi-innovation learning algorithm based on PID neural networks is presented, which can improve the online identification performance of the networks. The multi-innovation gradient type algorithms use the current data and the past d...

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Bibliographic Details
Main Authors: Gang Ren, Pinle Qin, Minmin Sun, Yan Lin
Format: Article
Language:English
Published: IFSA Publishing, S.L. 2013-05-01
Series:Sensors & Transducers
Subjects:
Multi-innovation
PID neural networks
System identification
Nonlinear system
Online Access:http://www.sensorsportal.com/HTML/DIGEST/may_2013/Special_issue/P_SI_356.pdf
id doaj-79ff97b34ddd4e36a86cf26ab58659b7
record_format Article
spelling doaj-79ff97b34ddd4e36a86cf26ab58659b72020-11-25T00:32:46ZengIFSA Publishing, S.L.Sensors & Transducers2306-85151726-54792013-05-0121Special Issue142146Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural NetworkGang Ren0Pinle Qin1Minmin Sun2Yan Lin3Ship CAD Engineer Center, Dalian University of Technology, Liaoling, ChinaShip CAD Engineer Center, Dalian University of Technology, Liaoling, China Department of Computer Science, North University of China, Shanxi, ChinaShip CAD Engineer Center, Dalian University of Technology, Liaoling, ChinaIn order to improve the identification accuracy of dynamic system, multi-innovation learning algorithm based on PID neural networks is presented, which can improve the online identification performance of the networks. The multi-innovation gradient type algorithms use the current data and the past data that make it more effective than the BP algorithm in view of accuracy and convergence rate. Simulation results showed that the proposed algorithm is effect.http://www.sensorsportal.com/HTML/DIGEST/may_2013/Special_issue/P_SI_356.pdfMulti-innovationPID neural networksSystem identificationNonlinear system
collection DOAJ
language English
format Article
sources DOAJ
author Gang Ren
Pinle Qin
Minmin Sun
Yan Lin
spellingShingle Gang Ren
Pinle Qin
Minmin Sun
Yan Lin
Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network
Sensors & Transducers
Multi-innovation
PID neural networks
System identification
Nonlinear system
author_facet Gang Ren
Pinle Qin
Minmin Sun
Yan Lin
author_sort Gang Ren
title Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network
title_short Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network
title_full Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network
title_fullStr Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network
title_full_unstemmed Convergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network
title_sort convergence analysis of multi-innovation learning algorithm based on pid neural network
publisher IFSA Publishing, S.L.
series Sensors & Transducers
issn 2306-8515
1726-5479
publishDate 2013-05-01
description In order to improve the identification accuracy of dynamic system, multi-innovation learning algorithm based on PID neural networks is presented, which can improve the online identification performance of the networks. The multi-innovation gradient type algorithms use the current data and the past data that make it more effective than the BP algorithm in view of accuracy and convergence rate. Simulation results showed that the proposed algorithm is effect.
topic Multi-innovation
PID neural networks
System identification
Nonlinear system
url http://www.sensorsportal.com/HTML/DIGEST/may_2013/Special_issue/P_SI_356.pdf
work_keys_str_mv AT gangren convergenceanalysisofmultiinnovationlearningalgorithmbasedonpidneuralnetwork
AT pinleqin convergenceanalysisofmultiinnovationlearningalgorithmbasedonpidneuralnetwork
AT minminsun convergenceanalysisofmultiinnovationlearningalgorithmbasedonpidneuralnetwork
AT yanlin convergenceanalysisofmultiinnovationlearningalgorithmbasedonpidneuralnetwork
_version_ 1725319155832324096

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