Supervisory Model Predictive Control for freeway traffic systems

The application of Model Predictive Control schemes to real world complex plants, such as freeway traffic systems, is sometimes limited because of the necessity of tuning the control action depending on the system operating condition, and the significant computational burden inherent to the methodology. The MPC-based scheme presented in this paper aims at overcoming the mentioned limitations by using a supervisory control approach. The supervisor, at each time step, chooses among three possible actions: i) the controller needs to be changed and the new control action is computed, ii) no change is made to the controller, but it is necessary to recompute the control action, iii) neither is the controller varied, nor it is necessary to recompute the control action and the already determined control law is kept. In other terms, the control sequence is recomputed according to an event-triggered mechanism in which the control action is properly tuned to the system conditions. In the paper, the proposed control scheme is developed with reference to a class of non-linear systems admitting a model of Mixed Logical Dynamical type, which is suitable to describe freeway traffic systems, and the input-to-state practical stability of the controlled system is proved. Finally, the application of the proposed control scheme to a freeway traffic system is discussed and studied via simulation.