Robust dissipative filtering for a kind of T-S fuzzy descriptor system with immeasurable premise variables

Dissipativity‐based adaptive integral sliding mode control of Takagi‐Sugeno fuzzy descriptor systems

“…[28] addressed the problem of dissipativity analysis for T‐S fuzzy descriptor time‐delay systems. Additionally, the delay‐dependent observer‐based control problem was discussed in [29], the delay‐dependent dissipative filtering problem was extensively studied in [30–32], and actuator saturation and disturbance problems were considered in [33]. The issues associated with dissipative analysis and fuzzy PDC controller design for T‐S fuzzy descriptor systems with different derivative matrices were investigated in [34].…”

“…First, it is difficult to implement complex non-linear systems in practice. The above studies [21][22][23][24][26][27][28][29][30][31][32][33] mainly discussed T-S fuzzy descriptor systems with the same derivative matrices E. Some studies [34][35][36] have shown that T-S fuzzy descriptor systems with different derivative matrices are more useful for modelling and analyzing the complexity of non-linear systems than T-S fuzzy descriptor systems with the same derivative matrices. Second, the conservativeness of the system stability criterion is increased.…”

“…As one of the most effective tools used to analyze the stability and performance of control systems, the dissipative theory provides a unified framework that encompasses existing results and some special cases, such as the H∞ performance and passivity performance. Therefore, the dissipative theory for T-S fuzzy descriptor systems has been widely investigated, such as in [28][29][30][31][32][33][34]. Han et al [28] addressed the problem of dissipativity analysis for T-S fuzzy descriptor time-delay systems.…”

“…The results [3-6, 26, 27] show that the controller based on the non-PDC method can effectively reduce conservativeness compared with the PDC method. In addition, some common Lyapunov functions are used to analyze the stability of T-S fuzzy descriptor systems in [21][22][23][24] and [28][29][30][31][32][33], which do not consider the relationship between subsystems and fuzzy membership functions. At the same time, it is difficult to find a common Lyapunov function for multiple subsystems, which leads to the conservatism of the method.…”

“…Uncertainties and exogenous disturbances are inevitable problems in non-linear systems in realistic environments. To address these challenges, researchers have applied different methods to compensate for uncertainties [21,26] and exogenous disturbances [22][23][24][27][28][29][30][31][32][33][34]. Notably, most of the literature did not address uncertainties and exogenous disturbances simultaneously.…”