Constrained Partial Form Dynamic Linearization Based Model Free Adaptive Perimeter Control for Urban Traffic Networks

The prevalent perimeter control methods currently employed to mitigate urban traffic congestion predominantly rely on the macroscopic fundamental diagram (MFD). It is extremely difficult to improve the performance of the urban traffic system in practice due to its complexity and uncertainty. In this paper, regarding the urban traffic system, a novel data driven control strategy known as constrained partial form dynamic linearization based model free adaptive control (cPFDL-MFAC) is offered. This method has the advantage of simply requiring the controlled urban traffic system's input and output (lID) data for designing the perimeter control strategies, as opposed to relying on the traffic dynamics model, and it can fully capture the intricacies of the dynamics present in the original system by partial form dynamic linearization data modeling technique. Moreover, the proposed method can also handle the constraint problems of control inputs and system outputs in urban transportation systems. The efficiency of the cPFDL-MFAC approach and its advantage over other widely utilized perimeter control strategies are verified via numerical simulation.