Modern times have seen an increasing use of networked control systems, in which plants and controllers may not necessarily have a direct link but instead be connected through a network, thereby closing control loops over multiple nodes.

The system may also be spread out spatially over a large area, and thus the associated network delays could greatly hamper control performance, potentially affecting the closed-loop stability of the system. In such scenarios, event-triggered control approaches could greatly reduce network congestion
by allowing a means for the controllers to send control loop computation packets over the network only when required, in an event-driven manner, rather than through periodic transmissions. However, in practice, the number of parallel channels is limited compared to the number of controllers and hence the transmission of packets needs to be scheduled carefully to avoid network conflicts.

This thesis explores using a network of timed (game) automata composed of models representing a networked control system’s control loops and its communication network. This reduces the scheduling problem of transmission of control loop computations to one of creating strategies using known algorithms, with the objective being to avoid network conflicts brought about by simultaneous transmissions. Furthermore, the proposed automata models also aim to reduce the conservatism of generated scheduling strategies by allowing the control loops a bounded number of retransmission attempts to send packets over the network in case it is already occupied. The concept is finally demonstrated in practice using simulated plants and controllers distributed over multiple machines connected via a physical CAN network.