Abstract In this article, we focus on the event‐triggered control problem for unknown continuous‐time linear systems under disturbances and input saturation within a data‐driven framework. A new adaptive event‐triggering mechanism (ETM) is proposed to preserve control performance. A key feature of this mechanism is the enforcement of a strictly positive minimum inter‐event time, which effectively eliminates Zeno behavior. By utilizing a sufficiently rich set of offline state measurements and inputs, a data‐driven representation of the unknown system is constructed. Additionally, a data‐driven stability criterion, formulated through the solution of linear matrix inequalities, is derived to ensure local stabilization of the system with unknown dynamics. A co‐design algorithm for data‐driven controllers and the ETM is developed to jointly optimize their parameters. Finally, the effectiveness of the proposed method is verified through numerical simulations.
Mu et al. (Sun,) studied this question.
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