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Enhanced speed control of BLDC motor using dwarf mongoose optimizer

  • Unique Paper ID: 164422
  • Volume: 10
  • Issue: 12
  • PageNo: 1484-1488
  • Abstract:
  • Brushless DC (BLDC) motors are popular in many applications due to their efficiency and performance characteristics. Precise control of BLDC motor speed is important for many industrial, automotive, and robotic applications. This article presents a new method to optimize BLDC motor speed control using Dwarf Mongoose Optimizer (DMO). DMO is an optimization resulting from the optimization of cooperative hunting of meerkats in the wild. In this work, we propose a framework that combines DMO with a Proportional Integral (PI) controller to optimize the speed control of BLDC motors. The DMO algorithm is used to tune the PI controller to optimum performance, including under speed reduction, time tuning, and steady-state operation while maintaining stability. Simulation results demonstrate the effectiveness of the DMO-based method to improve the speed control of BLDC motors. Compared with traditional tuning methods, the optimization controller exhibits better response and state accuracy. This research contributes to the field of motor control by demonstrating the ability of optimization techniques to optimize control, ultimately increasing efficiency, and resulting in better and more precise BLDC motors in various applications. Optimization of BLDC motor speed control has played an important role in improving the efficiency and performance of many electromechanical systems. In this study, we propose to use the optimization method called Dwarf Mongoose Optimizer to adjust and improve BLDC motor speed control. DMO is inspired by the social behaviour of meerkats, which demonstrate great abilities to find effective solutions to complex and non-linear problems. Our research focuses on the use of DMOs' ability to look for weak places and commit to best or near-perfect solutions. The proposed combination of BLDC motor speed control with DMO aims to increase accuracy, reduce power consumption, and improve overall performance compared to conventional valves. Through simulation and experimental validation, we evaluate the effectiveness of the proposed method, revealing its potential application in many industries where control of BLDC motors is essential for their good operation. The results demonstrate the effectiveness and eff
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 1484-1488

Enhanced speed control of BLDC motor using dwarf mongoose optimizer

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