Fuzzy-Tuned System Ident. & Control with Gradient Descent

Version 1.1.0 (106 KB) by Farrukh Nagi
Sugeno fuzzy-tuned system Identification and control with gradient descent method without Matlab fuzzy toolbox commands.
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Updated 11 Jan 2024

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Sugeno fuzzy-tuned system Identification and control with the gradient descent method [ H. Nomura,etal, 1991] is demonstrated in the examples. Stochastic and Batch gradient descent methods are used in the code. Gaussian function MFs are used with 25 and 49 rules. No matlab fuzzy toolbox commands are used to make the code convenient for conversion to other languages.
Note: If new system is to be identified or control the Gradient parameters are to be redefined.
Report any error or omission.

Cite As

Farrukh Nagi (2024). Fuzzy-Tuned System Ident. & Control with Gradient Descent (https://www.mathworks.com/matlabcentral/fileexchange/157391-fuzzy-tuned-system-ident-control-with-gradient-descent), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2021a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.1.0

Additional file
1.0.0