【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.更多还原

【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.更多还原