System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models

Zaidi, Salman

kassel university press, ISBN: 978-3-7376-0650-9, 2019, 150 Pages
(Schriftenreihe Mess- und Regelungstechnik der Universität Kassel 9)

URN: urn:nbn:de:0002-406517

DOI: 10.19211/KUP9783737606516

Zugl.: Kassel, Univ., Diss. 2018

| Price and available forms -->

Content: Some novel approaches to estimate Nonlinear Output Error (NOE) models using TS fuzzy models for a class of nonlinear dynamic systems having variability in their outputs is presented in this dissertation. Instead of using unrealistic assumptions about uncertainty, the most common of which is normality, the proposed methodology tends to capture effects caused by the real uncertainty observed in the data. The methodology requires that the identification method must be repeated offline a number of times under similar conditions. This leads to multiple inputoutput time series from the underlying system. These time series are preprocessed using the techniques of statistics and probability theory to generate the envelopes of response at each time instant. By incorporating interval data in fuzzy modelling and using the theory of symbolic interval-valued data, a TS fuzzy model with interval antecedent and consequent parameters is obtained. The proposed identification algorithm provides for a model for predicting the center-valued response as well as envelopes as the measure of uncertainty in system output.

Publication is available in following forms:

Full text (pdf-file, printable, with costs - 10.50 MB) 29.25 Euro
(free of charge in kassel University network - you are in kassel University network if you are in the workplace, or you are using a pc in the ITS or in the library)
download PDF - Attention! with costs, because you are not in kassel University network!