Adaptive event-triggered dissipative filtering for interval type-2 fuzzy semi-Markov jump systems with quantization and sensor failures.

In this work, the problem of affine parameter-based dissipative filtering is studied for interval type-2 fuzzy semi-Markov jump systems with consideration of quantization and sensor failures. In order to conserve the network resources, an adaptive event-triggered approach with network transmission delay is established between the sensor and filter for the decision to release sampled-data. By employing an affine parameter-based membership function, the conservativeness of the filtering model has been relaxed. In contrast to recent results, this approach effectively reduces the communication burden and enhances flexibility in managing sensor failures and disturbances. With the help of the Lyapunov stability theory, a new type of dissipative filtering approach is developed by constructing an asymmetric Lyapunov-Krasovskii functional and using recent integral inequalities in the main results. In particular, the stochastic stabilization criteria are obtained to achieve the weighting matrix and filtering parameters simultaneously by using the linear matrix inequality approach. Two numerical examples, including a tunnel diode circuit, are given to illustrate the merits of the developed approach.