# Adaptive Fuzzy Control MPPT algorithm for a PV

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Adaptive Fuzzy Control MPPT algorithm for a PV (Photovoltaic) boost DC-DC converter, which is used to track the maximum power point of a PV
Updated 19 Aug 2023

Adaptive Fuzzy Control MPPT algorithm for a PV (Photovoltaic) boost DC-DC converter, which is used to track the maximum power point of a solar panel. Here's a short explanation of how the code works:
1. Constants and Parameters: The code sets up the initial values for PV panel voltage, current, reference voltage, load resistance, capacitance, and various control parameters for the MPPT algorithm.
2. Fuzzy Logic Parameters: Defines the range of membership functions for error and change in error, as well as the control output range.
3. Initializing Control Parameters: Initializes the proportional (kp) and integral (ki) gains for the PI controller, as well as the integral term and previous error for integral control.
4. MPPT Loop: The main loop iterates for a specified number of time steps, simulating the MPPT process.
5. Error Calculation: Calculates the error as the difference between the reference voltage and the PV panel voltage. Also calculates the change in error.
6. Fuzzy Logic Controller: Utilizes the adaptiveFuzzyController function to compute the control output (u) based on fuzzy logic. This control output is used to adjust the duty cycle of the converter.
7. PI Control: Updates the integral term and calculates the duty cycle using both the fuzzy control output and the traditional PI control based on the error and integral term.
8. PV Panel Model: Updates the PV panel voltage and current based on the calculated duty cycle and load characteristics. This simulates the behavior of the boost DC-DC converter.
9. Storing Error: Stores the current error for the next iteration.
10. Final MPPT Voltage: Prints the final MPPT voltage after the simulation loop.
11. Fuzzy Logic Controller Function: The adaptiveFuzzyController function takes error and change in error as inputs and calculates the control output using fuzzy logic. It defines membership functions for error and change in error, uses Mamdani-type fuzzy inference rules, and calculates the control output by defuzzification.
12. Main Function: The adaptiveFuzzyMPPT function encapsulates the entire MPPT process and returns the final MPPT voltage.

### Cite As

PIRC (2024). Adaptive Fuzzy Control MPPT algorithm for a PV (https://www.mathworks.com/matlabcentral/fileexchange/133857-adaptive-fuzzy-control-mppt-algorithm-for-a-pv), MATLAB Central File Exchange. Retrieved .

##### MATLAB Release Compatibility
Created with R2022b
Compatible with any release
##### Platform Compatibility
Windows macOS Linux