Remote MPC for Tracking over Lossy Networks

In this work we consider the problem of remote control over lossy networks for systems subject to constraints. The objective is to devise a strategy for tracking reference signals while satisfying constraints under any network condition. We consider a remote Model Predictive Controller (MPC) and a local smart actuator able to stabilize the system when needed, in combination with a suitable mechanism to tackle packet losses. We show that the proposed algorithm allows us to enforce constraints without any assumption on the network, while we prove the convergence to constant desired references under mild assumptions. Simulations with real Wi-Fi communication data show the benefits of the algorithm with respect to other networked MPCs. The proposed solution is useful to combine high performances of advanced control technologies that cannot be implemented on-board and safety of locally controlled systems.