Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding Mode
In this paper, a radial basis neural network adaptive sliding mode controller (RBF−NN ASMC) for nonlinear electromechanical actuator systems is proposed. The radial basis function neural network (RBF−NN) control algorithm is used to compensate for the friction disturbance torque in the electromechan...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/4/1508 |
| _version_ | 1797395716161667072 |
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| author | Wei Ruan Quanlin Dong Xiaoyue Zhang Zhibing Li |
| author_facet | Wei Ruan Quanlin Dong Xiaoyue Zhang Zhibing Li |
| author_sort | Wei Ruan |
| collection | DOAJ |
| description | In this paper, a radial basis neural network adaptive sliding mode controller (RBF−NN ASMC) for nonlinear electromechanical actuator systems is proposed. The radial basis function neural network (RBF−NN) control algorithm is used to compensate for the friction disturbance torque in the electromechanical actuator system. An adaptive law was used to adjust the weights of the neural network to achieve real−time compensation of friction. The sliding mode controller is designed to suppress the model uncertainty and external disturbance effects of the electromechanical actuator system. The stability of the RBF−NN ASMC is analyzed by Lyapunov’s stability theory, and the effectiveness of this method is verified by simulation. The results show that the control strategy not only has a better compensation effect on friction but also has better anti−interference ability, which makes the electromechanical actuator system have better steady−state and dynamic performance. |
| first_indexed | 2024-03-09T00:38:35Z |
| format | Article |
| id | doaj.art-8789b7b8db9a4a15b9cd800c079fcab9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T00:38:35Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8789b7b8db9a4a15b9cd800c079fcab92023-12-11T17:57:32ZengMDPI AGSensors1424-82202021-02-01214150810.3390/s21041508Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding ModeWei Ruan0Quanlin Dong1Xiaoyue Zhang2Zhibing Li3School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, ChinaSchool of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, ChinaSchool of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, ChinaSchool of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, ChinaIn this paper, a radial basis neural network adaptive sliding mode controller (RBF−NN ASMC) for nonlinear electromechanical actuator systems is proposed. The radial basis function neural network (RBF−NN) control algorithm is used to compensate for the friction disturbance torque in the electromechanical actuator system. An adaptive law was used to adjust the weights of the neural network to achieve real−time compensation of friction. The sliding mode controller is designed to suppress the model uncertainty and external disturbance effects of the electromechanical actuator system. The stability of the RBF−NN ASMC is analyzed by Lyapunov’s stability theory, and the effectiveness of this method is verified by simulation. The results show that the control strategy not only has a better compensation effect on friction but also has better anti−interference ability, which makes the electromechanical actuator system have better steady−state and dynamic performance.https://www.mdpi.com/1424-8220/21/4/1508electromechanical actuator systemadaptive sliding mode controllerradial basis function neural network controllerfriction compensation |
| spellingShingle | Wei Ruan Quanlin Dong Xiaoyue Zhang Zhibing Li Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding Mode Sensors electromechanical actuator system adaptive sliding mode controller radial basis function neural network controller friction compensation |
| title | Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding Mode |
| title_full | Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding Mode |
| title_fullStr | Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding Mode |
| title_full_unstemmed | Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding Mode |
| title_short | Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding Mode |
| title_sort | friction compensation control of electromechanical actuator based on neural network adaptive sliding mode |
| topic | electromechanical actuator system adaptive sliding mode controller radial basis function neural network controller friction compensation |
| url | https://www.mdpi.com/1424-8220/21/4/1508 |
| work_keys_str_mv | AT weiruan frictioncompensationcontrolofelectromechanicalactuatorbasedonneuralnetworkadaptiveslidingmode AT quanlindong frictioncompensationcontrolofelectromechanicalactuatorbasedonneuralnetworkadaptiveslidingmode AT xiaoyuezhang frictioncompensationcontrolofelectromechanicalactuatorbasedonneuralnetworkadaptiveslidingmode AT zhibingli frictioncompensationcontrolofelectromechanicalactuatorbasedonneuralnetworkadaptiveslidingmode |