Adjacent Dynamic Linearization based Data-Driven Iterative Learning Control for Vehicle Formation

In this paper, a data-driven iterative learning control method based on dynamic linearization of adjacent vehicles is proposed for the formation control problem of connected autonomous vehicle (CAV) platoons. First, an adjacent dynamic linearization method is employed to establish a linear data model between two adjacent vehicles that communicate with each other. Then, by using the control knowledge originating from iterations, temporal information, and adjacent vehicles, an iterative learning formation control method is devised. The proposed control method is entirely data-driven, requiring no prior system model knowledge. Simulation results validate the efficacy of the developed approach.