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.
引用格式
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. 检索来源 .
MATLAB 版本兼容性
创建方式
R2021a
兼容任何版本
平台兼容性
Windows macOS Linux标签
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!