An event-triggered Model Predictive Control scheme for freeway systems

Objective of this paper is to define an efficient control framework for freeway systems based on ramp metering. First of all, a Model Predictive Control (MPC) scheme is proposed in which the well known nonlinear cell transmission model (CTM) is used for the prediction. The model is then reformulated as a mixed logical dynamical (MLD) system, i.e. it is described by linear dynamic equations and linear inequalities in which both continuous and binary variables are present. In this way, the finite-horizon optimal control problem in the MPC scheme is transformed into a mixed integer quadratic programming problem whose objective function quadratically penalizes the deviation of the state variables from a specific equilibrium point. It is shown that the resulting control law stabilizes the system. Moreover, in order to make it more suitable for a real-time use, the foregoing control strategy is redesigned into an event-triggered control scheme. The idea is to update the control law only when the considered error exceeds a pre-specified threshold. Simulation results demonstrate how the use of the triggering rule allows to preserve the good performance of the proposed control scheme, while reducing the overall computational load.