| Autor: |
Waleed Ahmad, Zain Ahmad Khan, Zaheer Alam, Umar Habib Khan, Izhar Ul Haq, Rashid Khan |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
2020 International Conference on Emerging Trends in Smart Technologies (ICETST). |
| Popis: |
This research article reports the designing of neuro-fuzzy based nonlinear generalized global sliding mode control (GGSMC) to track the globally maximum power point tracking (GMPPT) approach for partially-shaded photovoltaic system (PV) using buck-boost converter. In order to extract the possible maximum power (MP), it is compulsory to operate the PV system at maximum power point (MPP). GGSMC control scheme major advantages are faster convergence, high efficiency and robustness against the rapidly varying climatic conditions. The soft computing based technique neuro-fuzzy is utilized to generate the reference voltage for developed GMPPT control method. MATLAB/Simulink tool is used for simulations. The tracking performance of the proposed controller is compared with the previously conventional proportional integral derivative (CPID) controller. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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