Networked dynamical systems are found throughout the national infrastructure. Examples of such systems are seen in the national power grid, wastewater networks, and the national transportation system. As these networks grow in size, weak coupling across the network can blossom into system wide disturbances whose effects are felt over large geographical regions. There is, therefore, a compelling national need to devise more robust and cost-effective techniques for managing such networked systems. This project addresses this need through a self-triggered approach to decentralized control. In this approach, network subsystems use their current state information to determine the rate at which information must be exchanged to assure the networked system?s global L2 stability. These rates are cast as quality-of-service (QoS) constraints on the network?s traffic. This project uses these QoS constraints to develop soft real-time algorithms for scheduling message passing in networked control systems. The novel aspect of this work is that the resulting soft real-time control system provides guarantees on application performance that have traditionally been seen in hard real-time systems. The project is transferring the self-triggered technology to the private sector through collaborations with industry on a project that uses embedded sensor-actuator networks to control the frequency of combined-sewer-overflow (CSO) events. This CSO network is a good example of a networked cyber-physical system. To support the training of engineers qualified to manage such systems, this project is developing a set of lectures on the mathematical foundations of cyber-physical systems.
