Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive Control

This paper presents an implementation embedded system for position control of Permanent Magnet Synchronous Motor (PMSM). The control system consists of raspberry pi 3 as a microcontroller, ASDA-A2 servo drive, and Delta Servo ECMA type. The software design includes simulation tool and Python include...

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Main Authors: Ramelan Agus, Rohman Arief Syaichu, Kelana Allen
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201819804007
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spelling doaj-2604bdd9ffb44ef399a369648e8c7d162021-03-02T09:46:40ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011980400710.1051/matecconf/201819804007matecconf_meae2018_04007Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive ControlRamelan AgusRohman Arief SyaichuKelana AllenThis paper presents an implementation embedded system for position control of Permanent Magnet Synchronous Motor (PMSM). The control system consists of raspberry pi 3 as a microcontroller, ASDA-A2 servo drive, and Delta Servo ECMA type. The software design includes simulation tool and Python included on Raspbian OS. Communication between Raspberry Pi 3 and ASDA-A2 drivers using the ASCII Modbus communication protocol. Raspberry Pi 3 processes the reference data and the actual reading result and calculates the resulting error. The control algorithm used in this research is Model Predictive Control (MPC). As a Linear Quadratic Regulator, MPC aims to design and generate an optimal control signal with the ability to anticipate saturation, receding horizon, future event and take control accordingly In the design of the MPC technique to adjust the speed of the PMSM to take action of reference tracking, performance index optimization is done by adjusting the value of weighting horizon N, Q and R. The simulation and implementation results showed that the PMSM can reach the stability point on each desired setpoint and result in a near-zero steady-state error.https://doi.org/10.1051/matecconf/201819804007
collection DOAJ
language English
format Article
sources DOAJ
author Ramelan Agus
Rohman Arief Syaichu
Kelana Allen
spellingShingle Ramelan Agus
Rohman Arief Syaichu
Kelana Allen
Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive Control
MATEC Web of Conferences
author_facet Ramelan Agus
Rohman Arief Syaichu
Kelana Allen
author_sort Ramelan Agus
title Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive Control
title_short Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive Control
title_full Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive Control
title_fullStr Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive Control
title_full_unstemmed Embedded Position Control of Permanent Magnet Synchronous Motor Using Model Predictive Control
title_sort embedded position control of permanent magnet synchronous motor using model predictive control
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2018-01-01
description This paper presents an implementation embedded system for position control of Permanent Magnet Synchronous Motor (PMSM). The control system consists of raspberry pi 3 as a microcontroller, ASDA-A2 servo drive, and Delta Servo ECMA type. The software design includes simulation tool and Python included on Raspbian OS. Communication between Raspberry Pi 3 and ASDA-A2 drivers using the ASCII Modbus communication protocol. Raspberry Pi 3 processes the reference data and the actual reading result and calculates the resulting error. The control algorithm used in this research is Model Predictive Control (MPC). As a Linear Quadratic Regulator, MPC aims to design and generate an optimal control signal with the ability to anticipate saturation, receding horizon, future event and take control accordingly In the design of the MPC technique to adjust the speed of the PMSM to take action of reference tracking, performance index optimization is done by adjusting the value of weighting horizon N, Q and R. The simulation and implementation results showed that the PMSM can reach the stability point on each desired setpoint and result in a near-zero steady-state error.
url https://doi.org/10.1051/matecconf/201819804007
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AT rohmanariefsyaichu embeddedpositioncontrolofpermanentmagnetsynchronousmotorusingmodelpredictivecontrol
AT kelanaallen embeddedpositioncontrolofpermanentmagnetsynchronousmotorusingmodelpredictivecontrol
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