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@article{184812,
        author = {V SHARON and Suresha},
        title = {ANN BASED MODEL PREDICTIVE CONTROL OF INVERTER FOR POWER APPLICATION},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {3571-3577},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184812},
        abstract = {Ensuring high-quality and reliable AC power delivery from three-phase inverters with LC filters remains a significant challenge, particularly under nonlinear and dynamic load conditions. Conventional control strategies, such as proportional-integral (PI) controllers, often fail to achieve the necessary balance between low total harmonic distortion (THD), fast transient response, and computational efficiency. Although Model Predictive Control (MPC) has emerged as a robust solution due to its predictive optimization capability and superior voltage regulation, its substantial computational requirements hinder real-time implementation in high-frequency switching applications.This work proposes a hybrid control framework that integrates MPC with Artificial Neural Networks (ANN) to exploit the advantages of both approaches.},
        keywords = {Hybrid Control Strategy, Model Predictive Control, Artificial Neural Networks, Three-phase Inverter, LC Filter, Power Quality, Total Harmonic Distortion, Real-Time Implementation.},
        month = {September},
        }