Fuzzy T–S Model-Based Design of Min–Max Control for Uncertain Nonlinear Systems

  • Tatjana Kolemishevska-GugulovskaEmail author
  • Mile Stankovski
  • Imre J. Rudas
  • Nan Jiang
  • Juanwei Jing
Part of the Studies in Computational Intelligence book series (SCI, volume 657)


The min–max robust control synthesis for uncertain nonlinear systems is solved using Takagi–Sugeno fuzzy model and fuzzy state observer. Existence conditions are derived for the output feedback min–max control in the sense of Lyapunov asymptotic stability and formulated in terms of linear matrix inequalities. The convex optimization algorithm is used to obtain the minimum upper bound on performance and the optimum parameters of min–max controller. The closed-loop system is asymptotically stable under the worst case disturbances and uncertainty. Benchmark of inverted pendulum plant is used to demonstrate the robust performance within a much larger equilibrium region of attraction achieved by the proposed design.


Linear Matrix Inequality Fuzzy Model Inverted Pendulum Uncertain Nonlinear System Fuzzy Control System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The Authors gratefully acknowledge the crucial contribution by Professor Georgi M. Dimirovski in proving the theoretical results reported in this article.


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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Tatjana Kolemishevska-Gugulovska
    • 1
    Email author
  • Mile Stankovski
    • 1
  • Imre J. Rudas
    • 1
  • Nan Jiang
    • 1
  • Juanwei Jing
    • 1
  1. 1.SkopjeMacedonia

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