Neural Netw. 2025 Nov 25;196:108367. doi: 10.1016/j.neunet.2025.108367. Online ahead of print.
ABSTRACT
This study addresses the stabilization challenge of discrete-time Markovian jump systems (MJSs) in the presence of deception attacks by employing an event-triggered control (ETC) approach. The proposed ETC framework minimizes the frequency of data transmissions, thereby optimizing network bandwidth usage and mitigating congestion risks. Deception attacks, represented using a Bernoulli-distributed random variable, threaten system security by interfering with normal communication to extract sensitive information. To ensure mean-square stability of the considered MJS, sufficient conditions are established, and controller gain parameters are determined by solving linear matrix inequalities (LMIs). The effectiveness of the proposed method is demonstrated through two numerical examples, including an application to a DC motor system.
PMID:41349173 | DOI:10.1016/j.neunet.2025.108367
