Eco-Driving for Uncertain Nonlinear CAEVs Platoon via a Fully Distributed Adaptive Robust PID-Based Protocol

This article addresses the eco-driving control problem for uncertain nonlinear platoons of Connected Autonomous Electric Vehicles. To this aim, a double layer control architecture is exploited for the optimization of the whole platoon energy consumption via the computation of an energyefficient optimal trajectory which each vehicle has to track. The first layer leverages a Nonlinear Model Predictive Control for the computation of the ecological behavior, while the second layer is embedded via a novel fully distributed adaptive robust PID cooperative driving control. This latter is responsible of enforcing the precise leader-tracking of the followers vehicles, despite the presence of unmodeled dynamics, external disturbance and the lack of knowledge about the communication topology structure. Indeed, the combined action of the PIDlike protocol structure and the usage of adaptive gains makes the proposed solution very promptly in counteracting all the uncertain factors affecting the platoon dynamics. Stability analysis, carried out via Lyapunov theory, provides a Linear Matrix Inequality based gains tuning procedure and defines the proper control adaptation mechanism. The effectiveness of the approach is confirmed by virtual simulations in the high-fidelity platform Mixed Traffic Simulator.