Artificial intelligence based direct torque control of induction motor drive system
In this project, a three-phase Induction motor (IM) under the direct torque control (DTC) technique is studied. IM is known for its simple engines and its self-starter feature but it always suffered a setback in the area of torque and speed control as it is a highly coupled nonlinear plant and prove...
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2020
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/2604/1/KP%202020%20%28242%29.pdf |
| _version_ | 1796868679508426752 |
|---|---|
| author | Alhamin, Sarinah Binti Sim, Sy Yi Chien, Siong Kai Zambri, Nor Aira Mustafa, Farahiyah Alvin Lim, Meng Siang |
| author_facet | Alhamin, Sarinah Binti Sim, Sy Yi Chien, Siong Kai Zambri, Nor Aira Mustafa, Farahiyah Alvin Lim, Meng Siang |
| author_sort | Alhamin, Sarinah Binti |
| collection | UTHM |
| description | In this project, a three-phase Induction motor (IM) under the direct torque control (DTC) technique is studied. IM is known for its simple engines and its self-starter feature but it always suffered a setback in the area of torque and speed control as it is a highly coupled nonlinear plant and proves to be most complex and expensive speed drive. The application of direct torque control (DTC) is beneficial for fast torque reaction in IM but provide high torque and ripples due to harmonic effects. Thus, the speed control of induction motor is important to achieve maximum torque and efficiency. The aim of this study is to improve tracking performance of the induction motor drive using artificial intelligence control system. A method for controlling induction motor drive is presented with Proportional-Integral (PI) controller and Artificial Neural Networks (ANNs) for performance comparison. MATLAB/SIMULINK software is used to develop a three-phase 2 pole-cage type induction motor model. Also the performances of the two controllers have been verified in terms of its speed and torque responses. The ANN is trained so that the speed of the drive tracks the reference speed. This study proved that the performance and dynamics of the induction motor are enhanced using ANN controller as compared with PI controller. |
| first_indexed | 2024-03-05T21:43:24Z |
| format | Conference or Workshop Item |
| id | uthm.eprints-2604 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:43:24Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | uthm.eprints-26042021-10-25T06:06:08Z http://eprints.uthm.edu.my/2604/ Artificial intelligence based direct torque control of induction motor drive system Alhamin, Sarinah Binti Sim, Sy Yi Chien, Siong Kai Zambri, Nor Aira Mustafa, Farahiyah Alvin Lim, Meng Siang TK2000-2891 Dynamoelectric machinery and auxiliaries. Including generators, motors, transformers In this project, a three-phase Induction motor (IM) under the direct torque control (DTC) technique is studied. IM is known for its simple engines and its self-starter feature but it always suffered a setback in the area of torque and speed control as it is a highly coupled nonlinear plant and proves to be most complex and expensive speed drive. The application of direct torque control (DTC) is beneficial for fast torque reaction in IM but provide high torque and ripples due to harmonic effects. Thus, the speed control of induction motor is important to achieve maximum torque and efficiency. The aim of this study is to improve tracking performance of the induction motor drive using artificial intelligence control system. A method for controlling induction motor drive is presented with Proportional-Integral (PI) controller and Artificial Neural Networks (ANNs) for performance comparison. MATLAB/SIMULINK software is used to develop a three-phase 2 pole-cage type induction motor model. Also the performances of the two controllers have been verified in terms of its speed and torque responses. The ANN is trained so that the speed of the drive tracks the reference speed. This study proved that the performance and dynamics of the induction motor are enhanced using ANN controller as compared with PI controller. 2020 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/2604/1/KP%202020%20%28242%29.pdf Alhamin, Sarinah Binti and Sim, Sy Yi and Chien, Siong Kai and Zambri, Nor Aira and Mustafa, Farahiyah and Alvin Lim, Meng Siang (2020) Artificial intelligence based direct torque control of induction motor drive system. In: UNSPECIFIED. (Submitted) |
| spellingShingle | TK2000-2891 Dynamoelectric machinery and auxiliaries. Including generators, motors, transformers Alhamin, Sarinah Binti Sim, Sy Yi Chien, Siong Kai Zambri, Nor Aira Mustafa, Farahiyah Alvin Lim, Meng Siang Artificial intelligence based direct torque control of induction motor drive system |
| title | Artificial intelligence based direct torque control of induction motor drive system |
| title_full | Artificial intelligence based direct torque control of induction motor drive system |
| title_fullStr | Artificial intelligence based direct torque control of induction motor drive system |
| title_full_unstemmed | Artificial intelligence based direct torque control of induction motor drive system |
| title_short | Artificial intelligence based direct torque control of induction motor drive system |
| title_sort | artificial intelligence based direct torque control of induction motor drive system |
| topic | TK2000-2891 Dynamoelectric machinery and auxiliaries. Including generators, motors, transformers |
| url | http://eprints.uthm.edu.my/2604/1/KP%202020%20%28242%29.pdf |
| work_keys_str_mv | AT alhaminsarinahbinti artificialintelligencebaseddirecttorquecontrolofinductionmotordrivesystem AT simsyyi artificialintelligencebaseddirecttorquecontrolofinductionmotordrivesystem AT chiensiongkai artificialintelligencebaseddirecttorquecontrolofinductionmotordrivesystem AT zambrinoraira artificialintelligencebaseddirecttorquecontrolofinductionmotordrivesystem AT mustafafarahiyah artificialintelligencebaseddirecttorquecontrolofinductionmotordrivesystem AT alvinlimmengsiang artificialintelligencebaseddirecttorquecontrolofinductionmotordrivesystem |