A Complementary Modularized Ramp Metering Approach Based on Iterative Learning Control and ALINEA

被引：32

作者：

Hou, Zhongsheng ^{[1
]}

Xu, Xin

Yan, Jingwen ^{[1
]}

Xu, Jian-Xin ^{[2
,3
]}

Xiong, Gang ^{[4
]}

机构：

[1] Beijing Jiaotong Univ, Adv Control Syst Lab, Sch Elect & Informat Engn, Beijing 100044, Peoples R China

[2] Natl Univ Def Technol, Coll Mechatron & Automat, Inst Automat, Changsha 410073, Hunan, Peoples R China

[3] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 119260, Singapore

[4] Chinese Acad Sci, Automat Inst, Beijing 100080, Peoples R China

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2011年 / 12卷 / 04期

基金：

美国国家科学基金会;

关键词：

ALINEA; iterative learning control (ILC); ramp metering; traffic control; TRAFFIC FLOW;

D O I：

10.1109/TITS.2011.2157969

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Ramp metering is an effective tool for traffic management on freeway networks. In this paper, we apply iterative learning control (ILC) to address rampmetering in amacroscopic-level freeway environment. By formulating the original ramp metering problem as an output regulating and disturbance rejection problem, ILC has been applied to control the traffic response. The learning mechanism is further combined with Asservissement Lineaire d'Entree Autoroutiere (ALINEA) in a complementary manner to achieve the desired control performance. The ILC-based rampmetering strategy and the modified modularized ramp metering approach based on ILC and ALINEA in the presence of input constraints are also analyzed to highlight the advantages and the robustness of the proposed methods. Extensive simulations are given to verify the effectiveness of the proposed approaches.

引用

页码：1305 / 1318

页数：14

共 20 条

[11] Freeway ramp metering: An overview [J].