Surya Narayan Tripathy

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About

Surya Narayan Tripathy is a researcher specializing in the design, modeling, and control of permanent magnet brushless DC (BLDC) motors for advanced industrial and robotic applications. His work focuses on integrating intelligent optimization algorithms and fuzzy logic control to enhance motor performance, efficiency, and speed regulation. Notably, his 2022 paper on a "Dynamic Fuzzy-PID based Speed Controller for BLDC Motor" (4 citations) introduces a sophisticated MATLAB/SIMULINK model that improves starting and running conditions, demonstrating his expertise in hybrid control strategies. More recently, his 2024 study on the "Optimal design of a BLDC motor using African vulture optimization algorithm" (3 citations) pioneers the use of collective intelligence-based metaheuristics to minimize cost while maximizing torque and efficiency. Though early in his citation impact, Tripathy’s work represents a promising intersection of bio-inspired optimization and electric motor design, contributing to the growing demand for high-performance, energy-efficient drives in electric vehicles and robotics. His innovative application of the African vulture algorithm to motor design marks a notable achievement, positioning him as an emerging voice in sustainable electromechanical systems.