Fuzzy Model Identification for Control

Version 1.0.0.0 (1.25 MB) by Janos Abonyi
Several applications of fuzzy modeling
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Updated 14 Jul 2014

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MATLAB implentations of my book Fuzzy Model Identification for Control which was published in 2003.
The book present new approaches to the construction of fuzzy models for model-based control. New model structures and identification algorithms are described for the effective use of heterogeneous information in the form of numerical data, qualitative knowledge, and first principle models. The main methods and techniques are illustrated through several simulated examples and real-world applications from chemical and process engineering practice.

More information about the book at:
http://www.abonyilab.com/books/fmbook

Cite As

Janos Abonyi (2024). Fuzzy Model Identification for Control (https://www.mathworks.com/matlabcentral/fileexchange/47204-fuzzy-model-identification-for-control), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R14SP1
Compatible with any release
Platform Compatibility
Windows macOS Linux

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A3_Distill/

E2_1_TS_Siso/

E2_2_Ruspini/

E2_3_MMF/

E3_1_ZO_PH/

E3_2_Hamm/

E3_3_HFCM_PH/

E4_10_MMF_PH/

E4_11_HFCM_WH/model_analysis/

E4_11_HFCM_WH/model_simulation/

E4_13_FH_WH/

E4_2_Hamm(cont)/

E4_3_Mimodest/

E4_6_PriorLiq/

E4_8_BoxJenkins/

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E5_2_IMC_Liq/

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Fuzztions/

A3_Distill/

E3_3_HFCM_PH/

E4_10_MMF_PH/

E4_11_HFCM_WH/model_analysis/

E4_11_HFCM_WH/model_simulation/

E4_13_FH_WH/

E4_3_Mimodest/

E5_1_MMF_PH/

E5_1_MMF_PH/pid/

E5_2_IMC_Liq/

E5_3_MPC_Appl/

Version Published Release Notes
1.0.0.0