Decentralized Fuzzy Filter Design for Discrete‐Time Nonlinear Large‐Scale Systems with Uncertain Interconnections

ABSTRACT This paper presents decentralized fuzzy filter design techniques for discrete‐time nonlinear large‐scale systems with uncertain interconnections. The subsystems of the nonlinear large‐scale system and the decentralized filters are represented using Takagi–Sugeno (T–S) fuzzy model. Based on the closed‐loop system with estimation error, the decentralized fuzzy filter design problem is addressed to guarantee the filtering performance. A sufficient condition is derived to satisfy both the stability condition and the filtering performance, and its constructive condition is reformulated into various linear matrix inequality (LMI) formats. Finally, the effectiveness of the proposed methods and procedures is demonstrated through a simulation example. The main novelties of this paper can be broadly summarized into two points: First, the decentralized fuzzy filter design techniques are effectively proposed for uncertain interconnection by using the maximum interconnection bound. Second, the decentralized fuzzy filters are designed when the premise variable is not only measurable but also non‐measurable.