Adaptive event-triggered mechanism for networked control systems under deception attacks with uncertain occurring probability
Ali Kazemy, James Lam, Chang Zhao
Abstract
This paper addresses the problem of adaptive event-triggered control of nonlinear networked control systems under deception attacks. An adaptive event-triggered scheme has been utilised to reduce data transmissions via the communication channel. To model the occurrence of the random deception cyber-attacks on the transmitted data, a Bernoulli random variable is employed. Since the probability of occurrence of this random variable is not completely known in practice, this value is considered with uncertainty while almost all the existing methods consider it to be exactly known. By using the Lyapunov–Krasovskii method, sufficient conditions for the stability of the closed-loop system are derived and presented in terms of linear matrix inequalities. In the end, two illustrative examples are provided to demonstrate the effectiveness of the proposed method.