Smooth speed control of electric motor drive based on neural network method
This project aims to regulate the speed of permanent magnet synchronous motor (PMSM) by using the Neural Network. PMSM has been increasingly employed these days. However, there are large amounts of disturbances and uncertainties existing in PMSM speed regulation system, such as parameters variation,...
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2024
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sg-ntu-dr.10356-1769622024-05-24T15:44:19Z Smooth speed control of electric motor drive based on neural network method Lim, Aloysius Jun Liang Christopher H. T. Lee School of Electrical and Electronic Engineering chtlee@ntu.edu.sg Engineering This project aims to regulate the speed of permanent magnet synchronous motor (PMSM) by using the Neural Network. PMSM has been increasingly employed these days. However, there are large amounts of disturbances and uncertainties existing in PMSM speed regulation system, such as parameters variation, inverter nonlinearity, cogging torque and so on. Most of these factors may cause torque ripple, which is one of the most critical issues in PMSM system. This problem is expected to be solved by Neural Network because of its strong nonlinear fitting ability and self-learning ability. Hence, the disturbances can be obtained accurately and suppressed. This project allows student to develop an advanced electric motor control strategy from analysis, simulation, and evaluation. Bachelor's degree 2024-05-23T08:32:12Z 2024-05-23T08:32:12Z 2024 Final Year Project (FYP) Lim, A. J. L. (2024). Smooth speed control of electric motor drive based on neural network method. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176962 https://hdl.handle.net/10356/176962 en A1025-231 application/pdf Nanyang Technological University |
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Engineering Lim, Aloysius Jun Liang Smooth speed control of electric motor drive based on neural network method |
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This project aims to regulate the speed of permanent magnet synchronous motor (PMSM) by using the Neural Network. PMSM has been increasingly employed these days. However, there are large amounts of disturbances and uncertainties existing in PMSM speed regulation system, such as parameters variation, inverter nonlinearity, cogging torque and so on. Most of these factors may cause torque ripple, which is one of the most critical issues in PMSM system. This problem is expected to be solved by Neural Network because of its strong nonlinear fitting ability and self-learning ability. Hence, the disturbances can be obtained accurately and suppressed. This project allows student to develop an advanced electric motor control strategy from analysis, simulation, and evaluation. |
author2 |
Christopher H. T. Lee |
author_facet |
Christopher H. T. Lee Lim, Aloysius Jun Liang |
format |
Final Year Project |
author |
Lim, Aloysius Jun Liang |
author_sort |
Lim, Aloysius Jun Liang |
title |
Smooth speed control of electric motor drive based on neural network method |
title_short |
Smooth speed control of electric motor drive based on neural network method |
title_full |
Smooth speed control of electric motor drive based on neural network method |
title_fullStr |
Smooth speed control of electric motor drive based on neural network method |
title_full_unstemmed |
Smooth speed control of electric motor drive based on neural network method |
title_sort |
smooth speed control of electric motor drive based on neural network method |
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Nanyang Technological University |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/176962 |
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1800916251801812992 |