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Article Dans Une Revue IEEE Transactions on Automatic Control Année : 2024

Event-triggered control from data

Résumé

We present a data-based approach to design eventtriggered state-feedback controllers for unknown continuoustime linear systems affected by disturbances. By an event, we mean state measurements transmission from the sensors to the controller over a digital network. By exploiting a sufficiently rich finite set of noisy state measurements and inputs collected off-line, we first design a data-driven state-feedback controller to ensure an input-to-state stability property for the closed-loop system ignoring the network. We then take into account sampling induced by the network and we present robust data-driven triggering strategies to (approximately) preserve this stability property. The approach is general in the sense that it allows deriving data-based versions of various popular triggering rules of the literature. In all cases, the designed transmission policies ensure the existence of a (global) strictly positive minimum inter-event time thereby excluding Zeno phenomenon despite disturbances. These results can be viewed as a step towards plugand-play control for networked control systems, i.e., mechanisms that automatically learn to control and to communicate over a network.
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Dates et versions

hal-04299286 , version 1 (22-11-2023)

Identifiants

Citer

Claudio de Persis, Romain Postoyan, Pietro Tesi. Event-triggered control from data. IEEE Transactions on Automatic Control, In press, pp.Early Access. ⟨10.1109/TAC.2023.3335002⟩. ⟨hal-04299286⟩
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