2003 | OriginalPaper | Chapter
Fuzzy Models of Dynamical Systems
Author : János Abonyi
Published in: Fuzzy Model Identification for Control
Publisher: Birkhäuser Boston
Included in: Professional Book Archive
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Model-based engineering tools require the availability of suitable dynamical models. Consequently, the development of a suitable nonlinear model is of paramount importance. Given the high expectations of fuzzy models in the area of identification and control, it becomes necessary to analyze and extract control-relevant information from fuzzy models of dynamical processes. Hence, in this chapter after an introduction to the data-driven modeling of dynamical systems, the following characteristics of TS fuzzy models are analyzed: Fuzzy models of dynamical systemsState-space realization of the modelPrediction of the equilibrium pointsStability of the equilibrium pointsExtraction of a linear dynamical model around an operating point Based on this analysis, new fuzzy model structuresHybrid F\izzy Convolution ModelFuzzy Hammerstein Model are proposed; these models can more effectively represent special nonlinear dynamic processes than can conventional fuzzy systems.