Identification of dynamical systems with a robust interval fuzzy model

DOI10.1016/j.automatica.2004.09.010zbMath1116.93320OpenAlexW2072716740MaRDI QIDQ1764052

Igor Škrjanc, Saso Blažič, Osvaldo E. Agamennoni

Publication date: 23 February 2005

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2004.09.010

zbMATH Keywords

Linear programmingFuzzy modelInterval fuzzy modelMin-max optimization

Mathematics Subject Classification ID

Linear programming (90C05) Fuzzy control/observation systems (93C42) System identification (93B30) General methods in interval analysis (65G40)

Related Items (4)

An evolving concept in the identification of an interval fuzzy model of Wiener-Hammerstein nonlinear dynamic systems ⋮ Fuzzy confidence interval for pH titration curve ⋮ Stabilization of Rössler chaotic dynamical system using fuzzy logic control algorithm ⋮ PID controller design for nonlinear systems represented by discrete-time local model networks

Cites Work

• Unnamed Item
• Linear programming: foundations and extensions
• Necessary conditions for some typical fuzzy systems as universal approximators
• Robust control. Systems with uncertain physical parameters. In co-operation with A. Bartlett, D. Kaesbauer, W. Sienel, R. Steinhauser
• Fuzzy identification of systems and its applications to modeling and control
• Detection and Characterization of Cluster Substructure I. Linear Structure: Fuzzy c-Lines
• Detection and Characterization of Cluster Substructure II. Fuzzy c-Varieties and Convex Combinations Thereof
• Canonical piecewise-linear approximation of smooth functions
• Fuzzy systems as universal approximators
• High-level canonical piecewise linear representation using a simplicial partition

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