Fuzzy Peak-to-Peak Filtering for Networked Nonlinear Systems With Multipath Data Packet Dropouts

• Published in: IEEE transactions on fuzzy systems Vol. 27; no. 3; pp. 436 - 446
• Main Authors: Chang, Xiao-Heng, Liu, Qi, Wang, Yi-Ming, Xiong, Jun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computer simulation; Data models; Data packet dropout; Filtering; Filtration; Fuzzy systems; Linear matrix inequalities; Mathematical model; Matrix methods; networked systems; Nonlinear systems; peak-to-peak filtering; Performance analysis; Performance indices; Random variables; Stochastic processes; Takagi–Sugeno (T–S) fuzzy systems
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2018.2859903

In this paper, the peak-to-peak filtering problem is studied for a class of networked nonlinear systems. The nonlinear physical plant is represented by the Takagi-Sugeno fuzzy system. Assume that the data packet dropout phenomenon occurs when the measurement output signal and the performance output signal of the nonlinear systems are transmitted by the digital communication channel. Two stochastic variables satisfying the Bernoulli random binary distribution are used to model this phenomenon. The motive of this paper is to design a peak-to-peak filter such that the filtering error system is stochastically stable and the prescribed peak-to-peak performance index is guaranteed. The developed theoretical results for designing a peak-to-peak filter are expressed in the form of linear matrix inequalities. Finally, a simulation example is presented to illustrate the validity of theoretical analysis.