Iterative learning control with internal model for freeway ramp metering

In this work, we focus on tracking iteration-varying densities, which are described by an internal model between two consecutive iterations, with iterative learning control (ILC) based ramp metering. The internal model is used to construct the ILC law, which is different from the classical one. Rigorous analyses show that the revised ILC method can deal with the problem that the desired trajectories are iteration-depended. Intensive simulations validate the superiority of the new control strategy compared with the classical ILC.