Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6865469 | Neurocomputing | 2016 | 9 Pages |
Abstract
This study investigates decentralized fuzzy Hâ filtering for a class of network-based interconnected systems. The considered system has the following main features: (1) it is a nonlinear system approximated by a T-S fuzzy model; (2) subsystems are connected through wired or wireless networks and therefore signal transfer in/among subsystems is subject to communication delay and/or packet loss; and (3) the network transmission capacity is limited. A discrete decentralized event-triggering scheme (DDETS) is proposed to overcome the network bandwidth limitation, which can reduce data transmission in subsystems effectively. By employing the above main features and using the DDETS, a new system model is proposed. Then the Lyapunov functional approach is applied to development of two stability conditions (Theorem 1, Theorem 2), which are used to design filters and triggering matrices of each subsystem simultaneously. Finally, an example is used to demonstrate the application of the proposed method.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Engang Tian, Dong Yue,