Adaptive Event-Triggered Fuzzy Control for Unreliable Networked Control Systems with Time-Varying Delay

This paper aims to investigate an adaptive event-triggered control scheme for unreliable networked control systems with data loss, transmission delay, and time-varying delay described by Takagi–Sugeno (T–S) fuzzy model. In order to achieve higher computational efficiency, better robustness, and higher control accuracy, an adaptive event-triggered controller based a sampling-state error mechanism is proposed. The proposal of this scheme extends the adaptive range of the event-triggered controller. On the basis of linear matrix inequality (LMIs), a new stability criterion is attained under the Lyapunov–Krasovskii functional (LKF) theory. Compared with the previous results, the scheme is less conservative. By using a numerical system and a continuous stirred tank reactor (CSTR) system, the quantitative experimental results indicate that the number of sampling in the controller is reduced, thus verifying the effectiveness and superiority of this control method.