Extended dissipative truncated predictive control strategy for conic-type delayed networked control systems affected by cyber attacks and sensor distortion

This paper investigates a truncated predictive control (TPC) strategy for delayed conic-type nonlinear networked control systems (CNNCSs). The proposed framework addresses key issues such as sensor distortion, system uncertainty, extended dissipativity performance (EDP), and cyber-attacks. Specifically, cyber-attacks are modeled using a Bernoulli distribution, while sensor distortion is represented by a Markov jump system (MJS) model. To handle these challenges, lyapunov stability theory (LST) and linear matrix inequalities (LMIs) are employed to establish sufficient conditions that guarantee global stability of the networked control systems (NCSs). The TPC approach effectively manages the combined effects of nonlinearities, time delays, and network imperfections. By constructing a suitable Lyapunov–Krasovskii functional (LKF) and applying appropriate inequality techniques, the conditions are formulated in an LMI framework. The derived results ensure that CNNCSs maintain desired performance levels under adverse conditions. Finally, two numerical examples are presented to demonstrate the validity and effectiveness of the proposed method.