Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of Gravity
With the aim of correcting the problem of trajectory tracking control of a flexible joint space manipulator in environments with different gravity, a neural network adaptive inverse control algorithm based on singular perturbation theory is proposed to resist the disturbance caused by system uncerta...
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MDPI AG
2024-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/21/6942 |
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| author | Shaoqing Li Lingcong Meng Kai Fang Fucai Liu |
| author_facet | Shaoqing Li Lingcong Meng Kai Fang Fucai Liu |
| author_sort | Shaoqing Li |
| collection | DOAJ |
| description | With the aim of correcting the problem of trajectory tracking control of a flexible joint space manipulator in environments with different gravity, a neural network adaptive inverse control algorithm based on singular perturbation theory is proposed to resist the disturbance caused by system uncertainty. Firstly, the dynamic model of a flexible joint space manipulator with the influence of gravity is established, and then the system is divided into a fast subsystem and a slow subsystem using singular perturbation theory. The velocity feedback control rate is designed for the fast subsystem to suppress the elastic vibration caused by the joint flexibility. For the slow subsystem, the uncertain term and known term are separated by the inverse control algorithm, where the uncertain term is approximated online by the RBF neural network, and the robust control rate is designed to compensate for the approximation error. The simulation results show that the control method can not only effectively reduce the high-frequency vibration caused by the flexible joint but also resist the system disturbance so that a good track control effect is achieved. |
| format | Article |
| id | doaj-art-f0001646855945d6b977d2f459006c6c |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-f0001646855945d6b977d2f459006c6c2024-11-08T14:41:33ZengMDPI AGSensors1424-82202024-10-012421694210.3390/s24216942Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of GravityShaoqing Li0Lingcong Meng1Kai Fang2Fucai Liu3School of Mechanical and Electrical Engineering, Zhangjiakou Vocational and Technical College, Zhangjiakou 075000, ChinaKey Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, ChinaKey Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, ChinaKey Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, ChinaWith the aim of correcting the problem of trajectory tracking control of a flexible joint space manipulator in environments with different gravity, a neural network adaptive inverse control algorithm based on singular perturbation theory is proposed to resist the disturbance caused by system uncertainty. Firstly, the dynamic model of a flexible joint space manipulator with the influence of gravity is established, and then the system is divided into a fast subsystem and a slow subsystem using singular perturbation theory. The velocity feedback control rate is designed for the fast subsystem to suppress the elastic vibration caused by the joint flexibility. For the slow subsystem, the uncertain term and known term are separated by the inverse control algorithm, where the uncertain term is approximated online by the RBF neural network, and the robust control rate is designed to compensate for the approximation error. The simulation results show that the control method can not only effectively reduce the high-frequency vibration caused by the flexible joint but also resist the system disturbance so that a good track control effect is achieved.https://www.mdpi.com/1424-8220/24/21/6942flexible jointspace manipulatorgravityRBF neural networkinverse control |
| spellingShingle | Shaoqing Li Lingcong Meng Kai Fang Fucai Liu Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of Gravity Sensors flexible joint space manipulator gravity RBF neural network inverse control |
| title | Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of Gravity |
| title_full | Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of Gravity |
| title_fullStr | Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of Gravity |
| title_full_unstemmed | Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of Gravity |
| title_short | Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of Gravity |
| title_sort | neural network adaptive inverse control of flexible joint space manipulator considering the influence of gravity |
| topic | flexible joint space manipulator gravity RBF neural network inverse control |
| url | https://www.mdpi.com/1424-8220/24/21/6942 |
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