Distributed Fuzzy H_∞ Filtering for Nonlinear Multirate Networked Double-Layer Industrial Processes

The distributed fuzzy H_∞ filtering problems constitute addressed for a class of nonlinear multirate networked industrial processes in this paper. The nonlinear industrial plants are described by Takagi-Sugeno (T-S) fuzzy models, while the distributed sensor measurements are subject to network-induced delays, stochastic disturbances, and packet dropouts. The sensors of different sampling rates are divided into two groups with different network topologies, and the corresponding filters are designed based on the T-S modeling technique. The major aim is to guarantee the filtering error system to be stochastically stable with a prescribed H_∞ performance index by designing proper filter gains. Finally, the simulation studies of continuous stirred tank reactor (CSTR) system in networked double-layer architecture further demonstrate the proposed strategy.