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A Comparative Study of BLDC Motor Speed Control Using PI and ANN Regulator

Djamel Eddine Beladjine, Djamel Boudana, Abdelhafidh Moualdia, Mohamed Hallouz, Patrice Wira

202127 citationsDOI

Abstract

This article discusses a comparative study between classical PI control and Artificial Neural Network (ANN) based control of a brushless DC motor. BLDC is recommended for drives that require a large load torque, these types of motors are non-linear systems which require robust control. Due to the saturation characteristic presented by the conventional PI regulator which causes the instability of the system, we have used an artificial neuron-based controller to overcome these aspects and to provide a better dynamic and quick response, in order to control the speed of a BLDC motor as well as the reduction in torque ripples. Simulation results obtained using MATLAB / SIMULINK show that the artificial neuron network controller performance evaluation are better than those obtained by the standard PI controller.

Topics & Concepts

Control theory (sociology)Artificial neural networkTorquePID controllerComputer scienceController (irrigation)RegulatorElectronic speed controlControl engineeringMATLABDC motorVector controlInduction motorEngineeringControl (management)Artificial intelligenceVoltageTemperature controlPhysicsChemistryElectrical engineeringBiologyGeneOperating systemAgronomyThermodynamicsBiochemistrySensorless Control of Electric MotorsElectric Motor Design and AnalysisIndustrial Automation and Control Systems