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April 26, 2026International Transactions on Electrical Energy SystemsOpen Access

Optimal Design of AI Controller for Fuel Cell and Renewable Energy Integrated Parallel Inverters Using Lyre Bird Algorithm

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Authors

SGSravanthy GaddameedhiNKNirved KumarNSN. Susheela

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Overview

Randomized trial demonstrates improved power distribution in renewable energy inverters using AI optimization.

Key Points

  • This research aims to enhance power sharing and performance in parallel operated inverters for clean energy systems.
  • Introduced improved droop control (IDC) and an optimized artificial neural network controller (ANNC) using the lyrebird optimization algorithm (LOA).
  • Executed performance analysis in MATLAB/Simulink under balanced and unbalanced load conditions.
  • Conducted comparative analysis of the proposed controller versus traditional controllers like PIC, FLC, and SMC.
  • Enhanced power distribution efficiency among inverters, minimizing circulating currents and common-mode voltage.
  • Achieved constant DC link voltage under various solar power inputs with reduced total harmonic distortion.
  • Outperformed traditional controllers (PIC, FLC, SMC) based on performance metrics.

Cite This Study

Gaddameedhi et al. (2026) studied this question.

synapsesocial.com/papers/69edac9b4a46254e215b44fdhttps://doi.org/10.1155/etep/7935636
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