Model Free Adaptive Predictive Perimeter Control for an Urban Traffic Network

被引：0
|
作者：
Xu, Chunye [1 ]
Jin, Shangtai [1 ]
Ren, Ye [1 ]
Hou, Zhongsheng [1 ]
Wang, Danwei [2 ]
机构：
[1] Beijing Jiaotong Univ, Adv Control Syst Lab, Beijing 100044, Peoples R China
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
来源：
PROCEEDINGS OF 2018 IEEE 7TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE (DDCLS) | 2018年
关键词：
perimeter control; macroscopic fundamental diagram (MFD); model free adaptive predictive perimeter control (MFAPPC); HORIZON; CRITERIA;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Most exiting macroscopic fundamental diagram (MFD) based perimeter control methods are regarded as model-based feedback control methods, whose performance is hard to improve in practice due to the fact that traffic flow model is complex and has uncertainties. In this paper, a model free adaptive predictive perimeter control strategy is proposed for an urban traffic network. The control performance is improved by virtue of the prediction data model derived by dynamic linearization technique. The effectiveness of the proposed perimeter control algorithm is verified by comparing with the traditional PID controller in the simulation section.
引用
收藏
页码：374 / 379
页数：6
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