Fuzzy Remote Tracking Control for Randomly Varying Local Nonlinear Models Under Fading and Missing Measurements

Jun Song, Yugang Niu*, James Lam, Hak Keung Lam

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

73 Citations (Scopus)
40 Downloads (Pure)


This paper proposes a novel remote tracking control strategy for a class of discrete-time Takagi-Sugeno fuzzy systems with randomly occurring uncertainties and randomly varying local nonlinear models. The outputs of the fuzzy system are collected through an unreliable sensor subject to missing measurements. Simultaneously, the outputs of the remote models are transmitted to the controller through wireless channels, in which the fading measurements may inevitably happen. By considering the Rice fading model and the Markovian packet dropouts model, an output-feedback controller is designed such that the closed-loop fuzzy tracking system is robustly stochastically stable and a prescribed H remote tracking performance is achieved. Furthermore, sufficient conditions are obtained for the existence of admissible tracking controllers in terms of nonstrict linear matrix inequalities. To overcome the difficulty in computation, a modified cone-complementarity linearization algorithm is employed to cast the tracking controller design problem into a sequential minimization one, which can be readily solved by using standard numerical software. Simulation results demonstrate the effectiveness of the developed control algorithm for fuzzy remote tracking controller.

Original languageEnglish
Pages (from-to)1125-1137
Number of pages13
JournalIEEE Transactions on Fuzzy Systems
Issue number3
Publication statusPublished - Jun 2018


  • Fading measurement
  • fuzzy systems
  • missing measurement
  • remote tracking control


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