Hi,
I understand that you are looking for explanation of Fuzzy Artificial Neural Network.
Here's an overview of each block in a Simulink model of a Fuzzy Artificial Neural Network (FANN) controller:
- Fuzzy Inference System (FIS) Block: The FIS block contains the fuzzy logic rules and membership functions. It takes input signals from the Plant Model block and generates fuzzy output signals based on the defined rules. The FIS block uses fuzzy logic to map the inputs to appropriate linguistic variables and determine the appropriate control actions.
- Neural Network (NN) Block: The NN block represents the artificial neural network component of the FANN controller. It takes inputs from the FIS block and performs adaptive learning and control. The neural network learns from the input-output data and adjusts its weights and biases to optimize the control performance. The NN block can have multiple layers and various activation functions based on the specific neural network architecture chosen.
- Controller Block: The Controller block combines the outputs from the FIS block and the NN block to generate control signals. It can use simple mathematical operations, such as addition or multiplication, or more complex algorithms to combine the fuzzy and neural network outputs. The Controller block calculates the appropriate control actions based on the desired system behavior and the information provided by the FIS and NN blocks.
Hope this helps!
