Fuzzy-Tuned System Ident. & Control with Gradient Descent

Versión 1.1.0 (106 KB) por Farrukh Nagi
Sugeno fuzzy-tuned system Identification and control with gradient descent method without Matlab fuzzy toolbox commands.
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Actualizado 11 ene 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.
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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. Recuperado .

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Se creó con R2021a
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Versión Publicado Notas de la versión
1.1.0

Additional file
1.0.0