In this paper, an adaptive fuzzy model predictive control is developed for networked unknown nonlinear systems which are modeled by an interval type-2 (IT-2) Takagi–Sugeno (T–S) fuzzy method. By taking the effects of delay and packet loss occurrence in both network links as well as disturbance into account, the proposed controller is developed to ensure the stochastic stability with satisfied \({\mathcal{H}}_{2}\) and \({\mathcal{H}}_{\infty }\) performance indices and input constraints. For this purpose, by using Lyapunov analysis, adaptation laws are derived. In order to have some practical advantages, including the use of only one processor along with the controller as well as the use of less bandwidth, the adaptive block is implemented in the network channel. As a result, this block is designed in such a way that it does not need sensor data directly, but is formulated based on degraded data transmitted from the sensor link, which, of course, complicates the design calculations. Using the estimated parameters in the developed LMIs, the gain of the controller is updated in an on-line manner. Also, to avoid the excessive use of the communication links, an event-triggered mechanism is implemented before the sensors data transmission link. Finally, the effect of the proposed control approach is further demonstrated via two examples; a numerical example and also a practical example of an inverted pendulum.
