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    A novel control strategy for active power filters (APFs) uses a self-constructing Chebyshev fuzzy recurrent neural network (SCCFRNN) to effectively suppress harmonics. This advanced method improves modeling accuracy and reduces control burdens for better power quality.

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    Area of Science:

    • Electrical Engineering
    • Control Systems
    • Artificial Intelligence

    Background:

    • Active Power Filters (APFs) are crucial for mitigating harmonic distortions in power systems.
    • Accurate modeling of nonlinear dynamics in APFs is essential for effective harmonic suppression.
    • Existing control methods may face challenges with model uncertainties and computational complexity.

    Purpose of the Study:

    • To propose a novel complementary sliding mode (CSM) controller integrated with a self-constructing Chebyshev fuzzy recurrent neural network (SCCFRNN) for APF harmonic suppression.
    • To enhance the modeling accuracy of APF dynamics by approximating unknown nonlinear terms using SCCFRNN.
    • To reduce the control burden on the CSM controller (CSMC) through intelligent approximation.

    Main Methods:

    • Development of a SCCFRNN capable of automatic structure learning via a self-learning algorithm.
    • Integration of SCCFRNN with a CSM controller for harmonic suppression in APFs.
    • Utilizing adaptive laws for real-time adjustment of SCCFRNN parameters.
    • Leveraging the combined strengths of Fuzzy Neural Networks (FNN), Recurrent Neural Networks (RNN), and Chebyshev Neural Networks (CNN).

    Main Results:

    • The SCCFRNN effectively approximates unknown nonlinear dynamics within the APF model.
    • The proposed CSM controller with SCCFRNN demonstrates superior harmonic suppression capabilities.
    • Simulations and hardware experiments validate the feasibility and effectiveness of the control strategy.
    • The SCCFRNN-based approach offers advantages over conventional methods in terms of accuracy and reduced control complexity.

    Conclusions:

    • The proposed SCCFRNN-based CSM controller is a viable and superior solution for harmonic suppression in APFs.
    • The self-constructing nature of the SCCFRNN enhances adaptability and reduces the need for precise prior system knowledge.
    • This intelligent control approach contributes to improved power quality and system efficiency.