Reachability Analysis-based Interval Estimation for Discrete-time Takagi-Sugeno Fuzzy Systems

Shenghui Guo, Weijie Ren, Choon Ki Ahn, Chenglin Wen, Hak Keung Lam

Research output: Contribution to journalArticlepeer-review


Considering disturbances, noise, and sensor faults, this paper investigates interval estimation for discrete-time Takagi-Sugeno fuzzy systems. To obtain precise estimation results and attenuate disturbances and noise in the system simultaneously, we integrate robust observers based on the H technique and reachability analysis. Two novel observer gain computation methods are proposed for different purposes. The time-invariant method relaxes the original design conditions by transforming the parameterized linear matrix inequality into a series of linear matrix inequalities to increase computational speed, while the time-varying method employs the parameterized linear matrix inequality directly and conducts calculation online. Furthermore, reachable set representations for error dynamics are formulated by making use of both time-invariant observer gain and time-varying observer gain. Two comparative numerical simulation examples are studied to illustrate the effectiveness and superiority of the developed methods.

Original languageEnglish
JournalIEEE Transactions on Fuzzy Systems
Publication statusAccepted/In press - 2021


  • Estimation
  • Fuzzy systems
  • Interval estimation
  • Linear matrix inequalities
  • Numerical models
  • Observers
  • Reachability analysis
  • Takagi-Sugeno fuzzy systems
  • Takagi-Sugeno model
  • discrete-time systems
  • parameterized linear matrix inequality
  • reachability analysis
  • robust observer

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


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