Decentralized sampled-data H∞ fuzzy filtering for nonlinear interconnected systems with uncertain interconnections

Abstract

This paper is devoted to decentralized sampled-data $H_{\infty }$ fuzzy filtering with exponential time-variant gains (ETGs) for nonlinear interconnected systems subject to uncertain interconnections. Both the interconnected system and the desired decentralized filter are modeled as Takagi–Sugeno fuzzy systems. An alternative approach to the usual coordinate transformation method is introduced to design the fuzzy filter with ETGs by constructing a time- and tuning parameter-dependent function in the framework of aperiodic sampling. By the newly constructed function, a sufficient condition is established to ensure that the augmented error system is exponentially stable with an $H_{\infty }$ performance index. Based on the condition, a desired filter design including ETGs is developed in terms of linear matrix inequalities. Finally, through a simulation example, it is demonstrated that the alternative approach is effective for the filter design and the proposed filter can entail a visible extension of the sampling interval and an enhancement in the disturbance rejection.