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Performance enhancement of fuzzy-PID controller for MPPT of PV system to extract maximum power under different conditions

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Abstract

In this article, a maximum Power Point Tracking (MPPT) controller is designed for photovoltaic (PV) applications. This controller has been implemented with Fuzzy Gain Scheduling of Proportional–Integral–Derivative (PID) type controller (FGS-PID). To implement this controller, scaling factors (SF) for the input signals of FGS are applied. The recommended adaptive two-level controller has all the welfare of fuzzy logic system (FLC) and PID control. Zieglere–Nichols technique is used to fine-tune the initial PID’s gains. The PID’s gains are updated with FGS-PID in transient and steady-state conditions to cope with fluctuations, minimize settling time and ensure stability. FLC is used for gain factors to deal with tuning of conditioned input signals of the FGS-PID. Moreover, FLC and an improved shuffled frog leaping algorithm (ISFLA) are applied to tune the member functions (MFs) of FGS. The use of this algorithm can lead to automatic regulation of the triangular MFs. Simulations are done to confirm the edge of this approach over conventional methods. It is very fast and accurate in tracking the maximum power. It provides minimum oscillations and improved dynamic response than other approaches. The speed of the tracking is also improved with acceptable accuracy.

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Acknowledgements

This work was supported by Foundation of State Key Laboratory of Public Big Data (No.2023004), National Natural Science Foundation of China (No.61862051), the Science and Technology Foundation of Guizhou Province (No. ZK[2022]549), the Natural Science Foundation of Education of Guizhou province (No. [2019]203, No. KY[2019]067), and the Funds of Qiannan Normal University for Nationalities (No.qnsy2019rc09).

Funding

This study was not funded by any institution and organization.

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Authors and Affiliations

  1. School of Computer and Information, Qiannan Normal University for Nationalities, Duyun, 558000, Guizhou, China

    Tao Hai & Jincheng Zhou

  2. State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, Guizhou, China

    Tao Hai

  3. Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, China

    Tao Hai

  4. Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province, Duyun, 558000, China

    Jincheng Zhou

  5. Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan, Duyun, 558000, China

    Jincheng Zhou

  6. Solar Energy and Power Electronic Co, Ltd, Tokyo, Japan

    Noritoshi Furukawa

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  1. Tao Hai
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  2. Jincheng Zhou
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  3. Noritoshi Furukawa
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Correspondence to Jincheng Zhou or Noritoshi Furukawa.

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Appendix 1

Appendix 1

VMP = 168.65 V IMP = 4.94 A Voc = 22.32 V.

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Hai, T., Zhou, J. & Furukawa, N. Performance enhancement of fuzzy-PID controller for MPPT of PV system to extract maximum power under different conditions. Soft Comput 28, 2035–2054 (2024). https://doi.org/10.1007/s00500-023-09171-z

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