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Event-triggered dissipative filtering of fuzzy nonlinear dynamic systems

This paper focuses on the event-triggered dissipative reduced-order filter design problem for continuous-time Takagi-Sugeno (T-S) fuzzy systems. Firstly, the sufficient conditions are given to ensure the concerned filtering error system is asymptotic stability with (X, Y, Z)-θ-dissipative performance by utilizing the reciprocally convex approach and a novel Lyapunov-Krasovskii function. Afterwards, the relevant solvable conditions of the fuzzy-rule-dependent reduced-order filter are established which transform the desired reduced-order filter design into a solvable convex optimization problem by the means of employing the convex linearization method. Finally, a numerical example is given to demonstrate the applicability and validity of the proposed dissipative-based reduced-order filter design technique.