The neural network-based control system of direct current motor driver
This article aims to propose an adaptive control system for the direct current motor driver based on the neural network. The control system consists of two neural networks: the first neural network is used to estimate the speed of the direct current motor and the second neural network is used as a c...
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| Veröffentlicht in: | International journal of electrical and computer engineering (Malacca, Malacca) Malacca), 2019-04, Vol.9 (2), p.1445 |
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| container_title | International journal of electrical and computer engineering (Malacca, Malacca) |
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| creator | Nguyen, Trong-Thang |
| description | This article aims to propose an adaptive control system for the direct current motor driver based on the neural network. The control system consists of two neural networks: the first neural network is used to estimate the speed of the direct current motor and the second neural network is used as a controller. The plant in this research includes motor and the driver circuit so it is a complex model. It is difficult to determine the exact parameters of the plant so it is difficult to build the controller. To solve the above difficulties, the author proposes an adaptive control system based on the neural network to control the plant reach the high quality in the case of unknowing the parameters of the plant. The results are that the control quality of the system is very good, the response speed always follows the desired speed and the transition time is small. The simulation results of the neural network control system are shown and compared with that of a PID controller to demonstrate the advantages of the proposed method. |
| doi_str_mv | 10.11591/ijece.v9i2.pp1445-1452 |
| format | Article |
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The control system consists of two neural networks: the first neural network is used to estimate the speed of the direct current motor and the second neural network is used as a controller. The plant in this research includes motor and the driver circuit so it is a complex model. It is difficult to determine the exact parameters of the plant so it is difficult to build the controller. To solve the above difficulties, the author proposes an adaptive control system based on the neural network to control the plant reach the high quality in the case of unknowing the parameters of the plant. The results are that the control quality of the system is very good, the response speed always follows the desired speed and the transition time is small. 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The control system consists of two neural networks: the first neural network is used to estimate the speed of the direct current motor and the second neural network is used as a controller. The plant in this research includes motor and the driver circuit so it is a complex model. It is difficult to determine the exact parameters of the plant so it is difficult to build the controller. To solve the above difficulties, the author proposes an adaptive control system based on the neural network to control the plant reach the high quality in the case of unknowing the parameters of the plant. The results are that the control quality of the system is very good, the response speed always follows the desired speed and the transition time is small. 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| ispartof | International journal of electrical and computer engineering (Malacca, Malacca), 2019-04, Vol.9 (2), p.1445 |
| issn | 2088-8708 2088-8708 |
| language | eng |
| recordid | cdi_proquest_journals_2220191298 |
| source | EZB Electronic Journals Library |
| subjects | Adaptive control Computer simulation Control systems Controllers Direct current Driver circuits Network control Neural networks Parameters Proportional integral derivative |
| title | The neural network-based control system of direct current motor driver |
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