Stochastic Sampled-Data Fuzzy Security Control for Nonlinear Markov Jump Distributed Parameter Systems With Time-Varying Delay

This article focuses on the attack-tolerant and fault-tolerant cooperative fuzzy security control problem for nonlinear delayed Markov jump distributed parameter systems (DPSs) under the stochastic sampling that randomly switches between two sampling periods. First, a Takagi-Sugeno (T-S) fuzzy partial differential equation (PDE) model is presented to accurately describe the nonlinear delayed Markov jump DPSs. Subsequently, in consideration of possible random deception attacks and actuator faults, an attack-tolerant and fault-tolerant cooperative fuzzy security control approach with stochastic sampling is proposed under spatially point measurements (SPMs). Then, linear matrix inequality (LMI)-based sufficient conditions that guarantee the stochastically mean-square exponential stability of closed-loop nonlinear delayed Markov jump DPSs are obtained by employing a mode-dependent Lyapunov functional (LF). Lastly, two examples are given to illustrate the effectiveness of the presented control scheme.