Robust Stabilization for Discrete Networked Stochastic Switching LPV Models With Dos Attacks and Partly Known Semi-Markov Kernel

This paper investigates the robust stabilization for networked stochastic semi-Markov switching LPV models under random denial-of-service (DoS) attacks via a sliding mode control (SMC) approach. The semi-Markov kernel is partly known, given that the statistical properties of semi-Markov kernel are difficult to obtain completely. In contrast to the traditional Lyapunov function, the Lyapunov function is associated with the dwell time and the variable parameter. Since networked systems are subject to DoS attacks, a sliding mode with parameter variation is constructed to analyze the effects caused by cyber attacks. The system achieves the stability criterion based on the upper bound of dwell time and some techniques for removing nonlinear coupling terms by utilizing additional matrices. Finally, a turbofan engine model is introduced to validate the availability of the proposed method.