Abstract
This paper presents a model-based event-triggered (MB-ET) control framework for stabilization of networked systems. The controller and the events are designed in a decentralized manner, based only on local information. The knowledge of a priori model of the interconnected subsystems or agents is used at every controller node to generate estimates of the state of distant subsystems in order to reduce the frequency at which measurements need to be broadcasted. This framework allows for considerable reduction of bandwidth since every agent broadcasts its local information to other agents only when it is necessary, based on the difference between real and estimated variables. The use of models of the systems in the controller nodes not only generalizes the Zero-Order-Hold (ZOH) implementation in traditional event-triggered control schemes but it also provides stability thresholds that are robust to model uncertainties.
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