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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Indonesian Journal of Electrical Engineering and Computer Science
Boopathy, Kannan
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Control & Systems Engineering Electrical & Electronics Engineering

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Development and evaluation of artificial intelligence based maximum power point tracking for photovoltaic systems across diverse weather conditions Poornima, Penumala; Boopathy, Kannan
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i4.pp2443-2451

Abstract

An essential control mechanism for solar panels, maximum power point tracking (MPPT) constantly adjusts the operating point to maximize power extraction from changing environmental conditions, ensuring that the panels run at peak efficiency. To maximize energy yield, improve overall system performance, and add to the financial feasibility of solar installations, MPPT is crucial in today's energy landscape, which is increasingly focused on clean and renewable sources. In this study, we test four popular photovoltaic maximum power point tracking (MPPT) algorithms in different weather scenarios: perturb and observe (P&O), fuzzy logic, grey wolf optimizer (GWO), and horse herd optimization (HHO). Key parameters such as efficiency, responsiveness to partial shading, and adaptability to changing environmental conditions are analyzed using MATLAB models to evaluate each algorithm's performance in depth. The results show where each algorithm excels and where it falls short, and the research stands out by incorporating new features into the models. Our study seeks to provide valuable insights for the development of photovoltaic (PV) MPPT algorithms, guiding future research and applications in the ever-changing field of renewable energy systems. We will focus on making these algorithms more flexible in dynamic environments and resilient in partial shading situations.
Enhanced performance and efficiency of robotic autonomous procedures through path planning algorithm Latha, Raman; Sriram, Saravanan; Bharathi, Balu; Fernandes, John Bennilo; Raju, Ayalapogu Ratna; Boopathy, Kannan; Murugan, Subbiah
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp214-224

Abstract

To optimize surgical routes for better patient outcomes and more efficient operations, we want to test how well these algorithms work. Finding the best algorithms for different types of surgeries and seeing how they affect things like time spent in surgery, precision, and patient safety is the goal of this exhaustive study. By shedding light on the effectiveness of route planning algorithms, this work aspires to aid in the development of autonomous robotic surgery. To find out how well various algorithms work in actual surgical settings; this study compares them. The results of this work have the potential to enhance robotic surgery efficiency and improve surgical outcomes by informing the creation of more efficient route planning algorithms. The overarching goal of this study is to provide evidence that autonomous robotic surgery can benefit from using sophisticated route planning algorithms, which might lead to more accurate, faster, and safer procedures. The surgical patient dataset exhibits a wide variety of medical variables, including ages 38–62, weight 65–85 kg, height 160–180 cm, blood pressure 110–140/90 mm Hg, heart rate 70–85 bpm, hemoglobin 12–14 g/DL, and body mass index (BMI) 25.4–29.4.
Co-Authors Bharathi, Balu Fernandes, John Bennilo Latha, Raman Murugan, Subbiah Poornima, Penumala Raju, Ayalapogu Ratna Sriram, Saravanan