Reliable Sampling Mechanism for Takagi–Sugeno Fuzzy NCSs Under Deception Cyberattacks for the Application of the Inverted Pendulum System
Xiao Cai, Kaibo Shi, Kun She, Shouming Zhong, Yeng Chai Soh, Yue Yu
Abstract
This article investigates the stability problem of Takagi–Sugeno fuzzy networked control systems (TSNCSs) under deception cyberattacks via a reliable sampling mechanism, which has important research value for applications in network security. First, a fuzzy weight functional method is introduced, and a new Lyapunov–Krasovskii functional is developed, which better incorporates nonlinear problems in the model. Then, in order to reduce the initial constraints, improved time delay closed-loop functions are constructed that consider the delay information and the characteristics of the sampling time points. Furthermore, considering the reliability issues of controllers in real industry, we establish some sufficient conditions and implement a novel reliable sampling controller with deception attacks (DAs) to control the asymptotic stability of TSNCS. Finally, the correctness and feasibility of the proposed method are verified experimentally using an inverted pendulum system.