Sciweavers

Share
AUTOMATICA
2005

Identification of dynamical systems with a robust interval fuzzy model

9 years 9 months ago
Identification of dynamical systems with a robust interval fuzzy model
In this paper we present a new method of interval fuzzy model identification. The method combines a fuzzy identification methodology with some ideas from linear programming theory. On a finite set of measured data, an optimality criterion that minimizes the maximal estimation error between the data and the proposed fuzzy model output is used. The idea is then extended to modelling the optimal lower and upper bound functions that define the band that contains all the measurement values. This results in a lower and an upper fuzzy model or a fuzzy model with a set of lower and upper parameters. The model is called the interval fuzzy model (INFUMO). The method can be used when describing a family of uncertain nonlinear functions or when the systems with uncertain physical parameters are observed. We believe that the fuzzy interval model can be very efficiently used, especially in fault detection and in robust control design. 2004 Elsevier Ltd. All rights reserved.
Igor Skrjanc, Saso Blazic, Osvaldo E. Agamennoni
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2005
Where AUTOMATICA
Authors Igor Skrjanc, Saso Blazic, Osvaldo E. Agamennoni
Comments (0)
books