Data-Driven Construction of Sugeno Controllers: Analytical Aspects and New Numerical Methods

Ulrich Bodenhofer, Martin Burger, Josef Haslinger

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

In this paper, the general problem of identifying the parameters describing Sugeno controllers from example data is addressed. It is shown that this approximation is ill-posed, which necessitates the use of regularization methods. Based upon this discovery, an efficient numerical algorithm for solving the general regularized approximation problem is proposed, followed by numerical examples with real-world data.
Original languageEnglish
Title of host publicationProc. Joint 9th IFSA World Congress and 20th NAFIPS Int. Conf.
Pages239-244
Number of pages6
Publication statusPublished - Jul 2001

Fields of science

  • 101 Mathematics
  • 101020 Technical mathematics
  • 101004 Biomathematics
  • 101027 Dynamical systems
  • 101013 Mathematical logic
  • 101028 Mathematical modelling
  • 101014 Numerical mathematics
  • 101024 Probability theory
  • 102001 Artificial intelligence
  • 102003 Image processing
  • 102009 Computer simulation
  • 102019 Machine learning
  • 102023 Supercomputing
  • 202027 Mechatronics
  • 206001 Biomedical engineering
  • 206003 Medical physics
  • 102035 Data science

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