Event-Triggered Non-PDC Filter Design of Fuzzy Markovian Jump Systems under Mismatch Phenomena

Abstract

This paper focuses on dealing with the problem of co-designing a fuzzy-basis-dependent event generator and an asynchronous filter of fuzzy Markovian jump systems via event-triggered non-parallel distribution compensation (non-PDC) scheme. The introduction of the event-triggered non-PDC scheme can reduce the number of real-time filter gain design operations with a large computational load. Furthermore, to perform an effective relaxation process, several kinds of time-varying parameters in filter design conditions are simultaneously relaxed by utilizing two zero equalities of transition probabilities and mismatch errors. In addition, to improve the considered performance, the event generation function is established based on fuzzy-basis-dependent event weighting matrices.

Equivalent-Input-Disturbance Based Robust Control Design for Fuzzy Semi-Markovian Jump Systems via the Proportional-Integral Observer Approach

“…In contrast to MJSs, refs. [13][14][15][16] emphasized that the ST could follow more generic probability distributions. Therefore, compared to MJSs, SMJSs [17][18][19] have a wider range of practical application domains, and MJSs are thought to be more specific than SMJSs.…”

Peak-to-Peak Stabilization of Sampled-Data Systems Subject to Actuator Saturation and Its Practical Application to an Inverted Pendulum

“…It is important to note that IPSs, being mechanical systems, are inevitably influenced by persistent peak-bounded disturbances caused by external factors such as friction, vibrations, or shaking. However, as in [15][16][17][18], the majority of the sampled-data control techniques, designed using a loop functional approach, have mainly focused on attenuating the effects of energy-bounded disturbances while ensuring a guaranteed H ∞ performance. To deal with the problem of peak-bounded disturbances, as demonstrated in [19,20], is to consider the peak-to-peak performance, which allows for analyzing the ratio of the peak performance output to the peak disturbance input.…”

Admissibility and event-triggered dissipative observer-based stabilization of discrete-time T-S fuzzy singular systems via fuzzy Lyapunov functions

“…In addition, it has been known that T-S fuzzy models offer a good balance between accuracy, interpretability, and computational efficiency. Thus, owing to the advantage of T-S fuzzy models, a variety of stability analysis and control synthesis results have been reported for their extended systems such as Markovian jump fuzzy systems [22,9,21,27], T-S fuzzy fractional order systems [25,14,36,35], and T-S fuzzy singular systems (FSSs) [30,3,8,19]. Among them, the FSSs have been recognized as quite useful for describing T-S fuzzy systems with undefined behaviors and strict constraints caused by physical limitations, imprecise data, operational boundaries, and so on.…”