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Design of DC/DC Boost converter with FNN solar cell Maximum Power Point Tracking controller

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2 Author(s)
Hung-Ching Lu ; Department of Electrical Engineering, Tatung University, Taipei, Taiwan ; Te-Lung Shih

This paper demonstrates the Maximum Power Point Tracking (MPPT) controller that uses a DC/DC Boost converter with a Fuzzy Neural Network (FNN) system. It simplifies the topology of the DC/DC boost converter model to state equations, which is easy to simulate with Matlab. Additionally, the FNN system uses an integrated Fuzzy and Neural Network (NN), which advantages include uncertainty information processing and neural network learning. After assigning a suitable structure, we adjust the membership function and assign the algorithm weighting to track the maximum power point effectively in the parameters leaning process. The simulation result has verified the system to be efficient and rapid in tracking the MPP and converting the power from solar cells into the battery bank.

Published in:

2010 5th IEEE Conference on Industrial Electronics and Applications

Date of Conference:

15-17 June 2010