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带有迭代学习前馈的快速路无模型自适应入口匝道控制
引用本文:侯忠生,晏静文.带有迭代学习前馈的快速路无模型自适应入口匝道控制[J].自动化学报,2009,35(5):588-595.
作者姓名:侯忠生  晏静文
作者单位:1.北京交通大学电子信息工程学院先进控制系统研究所 北京 100044
基金项目:国家自然科学基金重点项目,国家自然科学基金面上项目 
摘    要:提出了一种新的带有迭代学习前馈的快速路无模型自适应入口匝道控制算法. 模块化的前馈迭代学习和反馈MFAC控制器设计方案使所设计的控制系统有效地利用了交通流的周期性特征, 提高了控制品质. 严格的数学推导证明了该方法的收敛性. 仿真研究及比较结果验证了所提算法的有效性.

关 键 词:迭代学习控制    无模型自适应控制    快速路匝道控制    收敛性分析    仿真研究
收稿时间:2008-3-24
修稿时间:2008-11-6

Model Free Adaptive Control Based Freeway Ramp Metering with Feedforward Iterative Learning Controller
HOU Zhong-Sheng YAN Jing-Wen.Advanced Control Systems Laboratory of School of Electronics , Information Engineering,Beijing Jiaotong University,Beijing.Model Free Adaptive Control Based Freeway Ramp Metering with Feedforward Iterative Learning Controller[J].Acta Automatica Sinica,2009,35(5):588-595.
Authors:HOU Zhong-Sheng YAN Jing-WenAdvanced Control Systems Laboratory of School of Electronics  Information Engineering  Beijing Jiaotong University  Beijing
Affiliation:1.Advanced Control Systems Laboratory of School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044
Abstract:In this work, a novel model-free adaptive control based freeway ramp metering strategy with feedforward iterative learning is proposed. The modularized controller design with feedforward iterative learning controller added on to the feedback model free adaptive control (MFAC) controller makes use of the periodicity of the traffic flow effectively and improves the controller performance greatly. With rigorous analysis, the proposed control scheme guarantees the asymptotic convergences along the iteration axis. Intensive simulations show the effectiveness of the proposed strategy.
Keywords:Iterative learning control (ILC)  model free adaptive control (MFAC)  freeway ramp metering  convergence analysis  simulation studies
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