We compare four variants of an event-based networked MPC approach with respect to computational effort and the amount of data transmitted across the network. In all four variants a local controller node evaluates an optimal affine feedback law and signals when this feedback law is no longer optimal. Upon this triggering event, a central compute node determines a new optimal feedback law along with its region of validity and sends it to the local node. The four variants compared here differ with respect to the amount of data that needs to be transmitted from the central to the local node, and with respect to the complexity of calculations required on the local node. We show that it suffices to transmit the active set of the optimal solution to the local node, if the local node is capable of carrying out a matrix inversion.
['Patrik Simon Berner', 'Martin Mönnigmann']
A comparison of four variants of event-triggered networked MPC