Скачать или смотреть MPPT Adaptive Neuro-Fuzzy Inference System (ANFIS) controller (Matlab/Simulink)

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The ANFIS uses a hybrid-learning rule combining back-propagation, gradient-descent, and least-squares algorithms to identify and optimize the Sugeno
system’s signals. The equivalent ANFIS architecture is a first-order Sugeno fuzzy model with 5*5 rules. The model has five layers and every node in a given layer has a similar function. The fuzzy IF-THEN rule set is used in which the outputs are linear combinations of their inputs . The anfisedit tool of MathWorks is used to create the ANFIS model based on our dataset.

The Steps are as follows:

Step #1: Loading data and normalization.
Step #2: Implement the fuzzy system using for example grid-partition (select the number of rules 5*5, the type of the membership function).
Step #3: Training the ANFIS model (number of epoch, error rate, etc.).
Step #4: Verify the performance (error measured versus estimated).