Robust Resource-Aware Self-Triggered Model Predictive Control

The wide adoption of wireless devices in the Internet Things requires controllers that are able to operate with limited resources, such as battery life. Operating these robustly an uncertain environment, while managing available increases difficultly controller design. This paper proposes a robust self-triggered model predictive control approach optimize objective resource consumption. In particular, novel zero-order-hold aperiodic discrete-time feedback law is developed ensure constraint satisfaction for continuous-time linear systems.