Improving the Performance of a Hierarchical Traffic Flow Control Framework Using Lyapunov-Based Switched Newton Extremum Seeking
Improving the Performance of a Hierarchical Traffic Flow Control Framework Using Lyapunov-Based Switched Newton Extremum Seeking
复制标题
使用基于李亚普诺夫的切换牛顿极值搜索提高分层交通流控制框架的性能
DOI：
10.1115/1.4064088
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Ghasemi, Amir H.
中科院分区：
文献类型：
--
作者：
Karimi Shahri, Pouria;HomChaudhuri, Baisravan;Ghaffari, Azad;Ghasemi, Amir H.
本研究的主要目的是提高基于基础设施的两级控制框架在扩展网络中用于流量管理的有效性。下层控制器调整车速，以达到上层控制器确定的期望密度。上层控制器采用一种新的基于Lyapunov的切换牛顿极值搜索控制方法，即使在模型中存在扰动的情况下，也能确定下游瓶颈未知的拥塞小区中的最优车辆密度。与基于梯度的方法不同，牛顿算法消除了对未知海森矩阵的需要，允许用户指定收敛速度。基于Lyapunov的切换方法也确保了渐近收敛到最优设置点。仿真结果表明，该方法结合了牛顿方法、用户可分配的收敛速度和基于Lyapunov的开关，在递阶控制框架下优于基于梯度的极值搜索。
The primary aim of this research paper is to enhance the effectiveness of a two-level infrastructure-based control framework utilized for traffic management in expansive networks. The lower-level controller adjusts vehicle velocities to achieve the desired density determined by the upper-level controller. The upper-level controller employs a novel Lyapunov-based switched Newton extremum seeking control approach to ascertain the optimal vehicle density in congested cells where downstream bottlenecks are unknown, even in the presence of disturbances in the model. Unlike gradient-based approaches, the Newton algorithm eliminates the need for the unknown Hessian matrix, allowing for user-assignable convergence rates. The Lyapunov-based switched approach also ensures asymptotic convergence to the optimal set point. Simulation results demonstrate that the proposed approach, combining Newton’s method with user-assignable convergence rates and a Lyapunov-based switch, outperforms gradient-based extremum seeking in the hierarchical control framework.