Iterative Learning Control with Forgetting Factor for Urban Road Network

In order to improve the traffic condition, a novel iterative learning control (ILC) algorithm with forgetting factor for urban road network is proposed by using the repeat characteristics of traffic flow in this paper. Rigorous analysis shows that the proposed ILC algorithm can guarantee the asympto...

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Main Authors: Tianyi Lan, Fei Yan, Hui Lin
Format: Article
Language:English
Published: Wiley 2017-01-01
Series:Journal of Control Science and Engineering
Online Access:http://dx.doi.org/10.1155/2017/9269187
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author Tianyi Lan
Fei Yan
Hui Lin
author_facet Tianyi Lan
Fei Yan
Hui Lin
author_sort Tianyi Lan
collection DOAJ
description In order to improve the traffic condition, a novel iterative learning control (ILC) algorithm with forgetting factor for urban road network is proposed by using the repeat characteristics of traffic flow in this paper. Rigorous analysis shows that the proposed ILC algorithm can guarantee the asymptotic convergence. Through iterative learning control of the traffic signals, the number of vehicles on each road in the network can gradually approach the desired level, thereby preventing oversaturation and traffic congestion. The introduced forgetting factor can effectively adjust the control input according to the states of the system and filter along the direction of the iteration. The results show that the forgetting factor has an important effect on the robustness of the system. The theoretical analysis and experimental simulations are given to verify the validity of the proposed method.
format Article
id doaj-art-e47c984d80834ec9adcfaf2a51435ef3
institution Kabale University
issn 1687-5249
1687-5257
language English
publishDate 2017-01-01
publisher Wiley
record_format Article
series Journal of Control Science and Engineering
spelling doaj-art-e47c984d80834ec9adcfaf2a51435ef32025-08-20T03:26:27ZengWileyJournal of Control Science and Engineering1687-52491687-52572017-01-01201710.1155/2017/92691879269187Iterative Learning Control with Forgetting Factor for Urban Road NetworkTianyi Lan0Fei Yan1Hui Lin2School of Automation, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaCollege of Information Engineering, Taiyuan University of Technology, Taiyuan, Shanxi 030024, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaIn order to improve the traffic condition, a novel iterative learning control (ILC) algorithm with forgetting factor for urban road network is proposed by using the repeat characteristics of traffic flow in this paper. Rigorous analysis shows that the proposed ILC algorithm can guarantee the asymptotic convergence. Through iterative learning control of the traffic signals, the number of vehicles on each road in the network can gradually approach the desired level, thereby preventing oversaturation and traffic congestion. The introduced forgetting factor can effectively adjust the control input according to the states of the system and filter along the direction of the iteration. The results show that the forgetting factor has an important effect on the robustness of the system. The theoretical analysis and experimental simulations are given to verify the validity of the proposed method.http://dx.doi.org/10.1155/2017/9269187
spellingShingle Tianyi Lan
Fei Yan
Hui Lin
Iterative Learning Control with Forgetting Factor for Urban Road Network
Journal of Control Science and Engineering
title Iterative Learning Control with Forgetting Factor for Urban Road Network
title_full Iterative Learning Control with Forgetting Factor for Urban Road Network
title_fullStr Iterative Learning Control with Forgetting Factor for Urban Road Network
title_full_unstemmed Iterative Learning Control with Forgetting Factor for Urban Road Network
title_short Iterative Learning Control with Forgetting Factor for Urban Road Network
title_sort iterative learning control with forgetting factor for urban road network
url http://dx.doi.org/10.1155/2017/9269187
work_keys_str_mv AT tianyilan iterativelearningcontrolwithforgettingfactorforurbanroadnetwork
AT feiyan iterativelearningcontrolwithforgettingfactorforurbanroadnetwork
AT huilin iterativelearningcontrolwithforgettingfactorforurbanroadnetwork