This study investigates a fuzzy consensus problem for nonlinear multi-agent systems (MASs) with parameter uncertainties via dynamic event-triggered mechanism. The interval type-2 (IT2) fuzzy systems are used to model MASs, and a dynamic event-triggered fuzzy controller is presented. A Lyapunov-Krasovskii functional is constructed in which the sampling property is included, based on which the sufficient condition is determined for dynamic event-triggered fuzzy controller, while all agents are guaranteed to be consensus exponentially. Finally, the MASs of tunnel diode circuit and one-link manipulator are used to verify the efficiency of the presented control method, respectively.

This manuscript is concerned with the problem of interval type-2 (IT2) fuzzy sampled-data $H_{\infty}$ control for nonlinear networked control systems with parameter uncertainties, data dropout and transmission delay. The IT2 fuzzy system used to describe the networked control systems and the IT2 networked sampled-data controller implemented by a zero-order holder is connected in closed-loop system. By means of the input delay approach, the resulting closed-loop system is converted into a continuous-time delayed system. Subsequently, the continuous- time Lyapunov-Krasovskii functional theory is used to carry out the stability analysis. Some slack matrices and the bound information in membership functions are introduced to obtain the relaxed sufficient conditions formed by the linear matrix inequalities, which guarantee the anticipant $H_{\infty}$ performance. Finally, the efficiency and merits of the proposed design method are verified by four practical systems.

This paper is devoted to the interval type-2 (IT2) fuzzy exponential stability for nonlinear networked sampled-data control systems with random communication links. By using the input delay approach, the designed networked IT2 fuzzy sampled-data controller can be applied in the continuous-time controlled plant, and the continuous-time Lyapunov-Krasovskii functional (LKF) is constructed. Based on the LKF theory, the stability analysis is conducted in the sense of mathematical expectation, and the sufficient conditions are determined in terms of the linear matrix inequalities. Then, the IT2 fuzzy networked controller is developed such that the networked closed-loop control system is exponentially stable. Finally, the simulation results are used to demonstrate the efficiency of the proposed design. The merits of the proposed algorithm are also shown by some comparative results.