Relaxed Resilient Fuzzy Stabilization of Discrete-Time Takagi–Sugeno Systems via a Higher Order Time-Variant Balanced Matrix Method - Xie, Xiangpeng; Wei, Cong; Gu, Zhou; Shi, Kaibo (IEEE transactions on fuzzy systems, 2022)
Resilient fuzzy stabilization is capable of providing much less conservative results than conventional fuzzy stabilization while the alert threshold condition should be always satisfied at each sampling instant. In order to make the alert threshold condition more easily to be guaranteed, the short paper employs the switching-type gain-scheduling control law so that the real-time information, which is specific to the current sampling instant, can be integrated into resilient fuzzy stabilization. More importantly, a new kind of time-variant balanced matrix is introduced for the first time for adjusting positive/negative terms of different monomials in a more flexible way. As a result, the conservatism of resilient fuzzy stabilization can be further reduced even if the alert threshold condition becomes more difficult to be violated. Finally, the advantage of the developed method is tested and validated via related comparisons on a benchmark example.