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Field programmable gate array-based neural network control strategy for computer power supply applications.

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  • 1Department of Electrical and Electronics Engineering, SASTRA Deemed University, Thanjavur, 613401, Tamil Nadu, India.

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Summary
This summary is machine-generated.

This study introduces a novel Multiple Output Switched Mode Power Supply (MOSMPS) using Artificial Neural Network (ANN) control to enhance power quality and voltage regulation in personal computers.

Keywords:
Artificial neural network (ANN)Bridgeless converterFPGAPower factor correction (PFC)Power quality (PQ)

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Area of Science:

  • Electrical Engineering
  • Power Electronics
  • Control Systems

Background:

  • Conventional Switched Mode Power Supplies (SMPS) often suffer from power quality issues and conduction losses.
  • Diode bridge rectifiers in traditional designs contribute to reduced efficiency and increased heat dissipation.
  • Personal computers require stable and efficient power delivery with high power quality.

Purpose of the Study:

  • To propose and validate a novel Multiple Output Switched Mode Power Supply (MOSMPS) for personal computers.
  • To improve Power Quality (PQ) and output voltage regulation using Artificial Neural Network (ANN) control.
  • To minimize conduction losses and enhance thermal management by eliminating the diode bridge rectifier.

Main Methods:

  • A bridgeless converter topology operating in Discontinuous Conduction Mode (DCM) was designed and modeled.
  • An Artificial Neural Network (ANN) controller was developed for advanced control strategy implementation.
  • The proposed MOSMPS with ANN control was simulated and experimentally verified using an FPGA processor.
  • Performance was evaluated based on Power Quality (PQ) indices and compared against conventional methods.

Main Results:

  • The proposed MOSMPS with ANN control demonstrated significant improvements in Power Quality (PQ) and output voltage regulation.
  • Operation in Discontinuous Conduction Mode (DCM) facilitated zero-current switching and improved Power Factor (PF).
  • The bridgeless topology effectively reduced conduction losses and enhanced thermal performance.
  • Experimental results validated the simulation models and the efficacy of the ANN controller.

Conclusions:

  • The proposed MOSMPS topology integrated with an ANN controller offers a superior solution for personal computer power supplies.
  • The design effectively addresses Power Quality (PQ) concerns and improves overall system efficiency.
  • The bridgeless converter and ANN control strategy provide a robust and efficient power management system.