Adaptive Event-Triggered Sampled-Data Fuzzy Security Control for Nonlinear Delayed DPSs With DoS Attacks and Stochastic Actuator Failures

This article addresses adaptive event-triggered sampled-data (SD) fuzzy security control under spatially local averaged measurements (LAMs) for nonlinear delayed distributed parameter systems (DPSs) with denial of service (DoS) attacks and stochastic actuator failures. Firstly, a Takagi-Sugeno (T-S) fuzzy model of delayed partial differential equations (PDEs) is introduced to precisely characterize the dynamic behavior of nonlinear delayed DPS. Secondly, an adaptive event-triggered SD fuzzy security control strategy is designed under DoS attacks and stochastic actuator failures, which can be flexibly modified in accordance with the present sampling and the most recently transmitted signals, and is implemented utilizing a restricted number of sensors and actuators. Subsequently, by establishing a Lyapunov functional, sufficient conditions that guarantee the mean square exponential stability of closed-loop nonlinear delayed DPSs are obtained based on linear matrix inequalities (LMIs). Finally, two examples are provided and the presented controller are compared to demonstrate the applications and advantages of the proposed approach. Note to Practitioners—Cyber-attacks, time-delays, and stochastic actuator failures have always been of great concern in security control because they occur frequently in practical DPSs. Consequently, when the DPSs is affected by these factors, it can lead to degraded performance and even system instability. In particular, existing security control strategies for DPSs are now based almost on time-triggered or regular event-triggered control mechanisms, resulting in high operating costs for security controllers. To overcome the challenge, adaptive event-triggered SD fuzzy security control strategy is proposed in this paper. By utilizing appropriate Lyapunov functional and inequality techniques, the proposed method in this paper novelty translates the problem of adaptive event-triggered SD fuzzy security controller design into a standard LMI feasibility problem. Several numerical examples are given to show the effective of the proposed control method, which contain the temperature regulation for a high-speed aerospace vehicle via the proposed control strategy. With the method proposed in this paper, the adaptive event-triggered SD fuzzy security controller requires only a small number of measurements to enable good performance when subjected to cyber-attacks, time-delays, and stochastic actuator failures, with significant cost savings, which is important for the improvement of stability and performance of nonlinear delayed DPSs.