Augmented input-output finite time stabilization and tracking control for networked control systems via adaptive event-triggered mechanism

The output tracking control issues for the networked control systems with a limited network communication are examined subject to time-varying delay and external disturbances. An event-triggered mechanism is integrated with a tracking control technique to reduce frequent data transmissions and to guarantee that the system output closely tracks the desired reference signal. Specifically, this event-trigger based tracking control mechanism transmits minimally required sampled data based on an adaptive triggering law to maintain satisfactory tracking performance. In order to estimate the state dynamics of considered systems, the non-fragile proportional integral observer implemented within event-triggered framework. This approach offers improved robustness in estimation compared to traditional observers. The tracking and state estimation objectives are converted into input-output finite time stabilization problem of the augmented closed-loop system. This transformation allows the unification of multiple control goals such as tracking performance and observer convergence into a single, well-structured mathematical framework. Furthermore, the required stabilization conditions to achieve output tracking and state estimation under network communication constraints and external disturbances are developed. These conditions are formulated as linear matrix inequalities, based on a suitably selected augmented Lyapunov-Krasovskii functional. Finally, the validity of the established results is verified through two numerical examples.