Event-Triggered Fuzzy Filtering for Nonlinear Dynamic Systems via Reduced-Order Approach

This paper is concerned with the problem of general-ized H-2 reduced-order filter design for continuous Takagi-Sugeno fuzzy systems using an event-triggered scheme. For a continuous Takagi-Sugeno fuzzy dynamic system, a reduced-order filter is designed to transform the original model into a linear lower order one. This filter can also approximate the original system with H-2 performance, with a new type of event-triggered scheme used to decrease the communication loads and computation resources within the network. By transforming the filtering problem to a convex optimization one, conditions are presented to design the fuzzy reduced-order filter. Finally, two illustrative examples are used to verify the feasibility and applicability of the proposed design scheme.