Abstract
In this letter, a model-free co-design scheme of triggering-driven controller is proposed for probabilistic Boolean control networks (PBCNs) in order to achieve feedback stabilization with minimum controller efforts. Specifically, Q-learning (QL) algorithm is exploited to devise a self-triggered strategy wherein the controller update time is computed in advance by using the current state information. A new self-triggered QL (STQL) algorithm is presented to achieve the co-design of feedback controller and self-triggered scheme rendering the closed-loop system stable at a given equilibrium point. Finally, some examples are presented to demonstrate the effectiveness of the proposed method.
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