Fuzzy Resilient Energy-to-Peak Filtering for Continuous-Time Nonlinear Systems

Abstract

The problem of resilient energy-to-peak filtering for a class of uncertain continuous-time nonlinear systems is investigated in this paper. A Takagi-Sugeno fuzzy model with norm-bounded uncertainties is used to represent the nonlinear plant. Attention is focused on the design of an energy-to-peak filter such that the filtering error system is asymptotically stable and the prescribed energy-to-peak filtering performance is guaranteed, where the designed filter is assumed to have additive gain variations. The proposed design is aimed at all filter matrices with gain variations, which improves the existing results on resilient energy-to-peak filtering for continuous-time systems. A simulation example is provided to show the effectiveness of the proposed methods.