摘要
针对快速路交通系统复杂时变以及难以建模的特点,首先,本文设计了基于无模型自适应预测控制的快速路入口匝道控制方案.其次,根据快速路交通系统具有重复性特点,本文在无模型自适应预测控制方法的基础上引入开环迭代学习控制,提出一种带有迭代学习前馈外环的无模型自适应入口匝道预测控制方案.相比无模型自适应预测控制方案,该方案可以利用迭代学习前馈控制器补偿系统可重复扰动,实现系统的完全跟踪.值得说明的是,预测控制器和学习控制器可以独立工作也可以联合工作.最后,文章给出了控制方案的收敛性分析,并通过交通流仿真验证了所提控制方案的有效性.
In view of the complexity,time-varying and modeling difficulty of freeway traffic systems,a ramp metering control scheme based on the model free adaptive predictive control is designed.Secondly,according to the repeatability of freeway traffic systems,a model free adaptive ramp metering predictive control scheme(MFAPC+ILC)with iterative learning feedforward outer-loop is proposed for performance enhancement.Compared with the model free adaptive predictive control scheme,the MFAPC+ILC control scheme can use the learning mechanism to compensate the repeatable disturbance of the systems and realize the perfect tracking of the systems.It is worth noting that predictive controller and learning controller can work independently or jointly.Finally,the convergence analysis of the proposed scheme is given,and the effectiveness of the scheme is verified by the traffic flow simulation.
作者
张茂帅
侯忠生
ZHANG Mao-shuai;HOU Zhong-sheng(School of Automation,Qingdao University,Qingdao Shandong 266071,China)
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2023年第5期781-791,共11页
Control Theory & Applications
基金
国家自然科学基金项目(61833001)资助。
关键词
无模型自适应预测控制
迭代学习控制
反馈前馈控制
快速路交通控制
匝道控制
model free adaptive predictive control
iterative learning control
feedback feedforward control
freeway traffic control
ramp metering
