Fuzzy Tracking Control for Nonlinear Networked Systems

Hongyi Li, Chengwei Wu, Xingjian Jing, Ligang Wu

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

159 Citations (Scopus)

Abstract

This paper studies the observer-based tracking control problem for discrete-time nonlinear networked control systems with parameter uncertainties and unmeasurable state variables. A network-induced constraint, i.e., the intermittent measurement loss, is considered in the controller design. The uncertain nonlinear system is described by an interval type-2 (IT2) fuzzy Takagi-Sugeno model, in which the lower and the upper membership functions with corresponding coefficients are used to capture and express uncertainties existing in the system. A premise-variables-independent IT2 fuzzy observer is constructed to estimate the unmeasurable state variables, and then a novel IT2 fuzzy tracking controller is designed. Furthermore, sufficient criteria are established to guarantee the resulting closed-loop system to be stochastically stable. Finally, two examples are provided to show the effectiveness of the proposed approach.

Original languageEnglish
Pages (from-to)2020-2031
Number of pages12
JournalIEEE Transactions on Cybernetics
Volume47
Issue number8
Online published19 Sept 2016
DOIs
Publication statusPublished - Aug 2017
Externally publishedYes

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 61622302, Grant 61673072, Grant 61525303, Grant 61573070, and Grant 61333012, in part by the Program for New Century Excellent Talents in University under Grant NCET-13-0696, in part by the Heilongjiang Outstanding Youth Science Fund under Grant JC201406, in part by the Fok Ying Tung Education Foundation under Grant 141059, and in part by the Natural Science Foundation of Liaoning Province under Grant 2015020049. This paper was recommended by Associate Editor S.-F. Su.

Research Keywords

  • Interval type-2 (IT2) fuzzy model
  • nonlinear networked control systems (NCSs)
  • observer-based tracking control
  • DISCRETE-TIME-SYSTEMS
  • SLIDING MODE CONTROL
  • LOGIC SYSTEMS

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