A Data-Driven Iterative Feedback Tuning Approach of ALINEA for Freeway Traffic Ramp Metering With PARAMICS Simulations

被引：46
|
作者：
Chi, Ronghu [1 ]
Hou, Zhongsheng [2 ]
Jin, Shangtai [2 ]
Wang, Danwei [3 ]
Hao, Jiangen [2 ]
机构：
[1] Qingdao Univ Sci & Technol, Sch Automat & Elect Engn, Qingdao 266042, Peoples R China
[2] Beijing Jiaotong Univ, Adv Control Syst Lab, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
[3] Nanyang Technol Univ, EXQUISITUS, Ctr E City, Sch Elect Elect Engn, Singapore 639798, Singapore
来源：
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | 2013年 / 9卷 / 04期
基金：
美国国家科学基金会; 新加坡国家研究基金会;
关键词：
ALINEA control; data-driven approach; FL-ALINEA; iterative feedback tuning; PARAMICS simulator; FLOW; OPTIMIZATION; MODEL;
D O I：
10.1109/TII.2013.2238548
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this work, a new iterative feedback tuning approach is proposed to tune ALINEA's controller gain automatically when there is not enough prior information available to select a proper feedback gain of ALINEA. It is a data-driven method and the ALINEA controller is auto-tuned only depending on the input and output data collected from closed-loop experiments. To mimic a real traffic environment, a simulator is built on the PARAMICS platform. The flow-based ALINEA controller is also considered to illustrate the good tuning performance of IFT comprehensively. The effectiveness of the proposed methods is verified through PARAMICS based simulations.
引用
收藏
页码：2310 / 2317
页数：8
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