Adaptive PD Neural Network Tracking Control for the Uncertain Robot Manipulator with Unmatched Disturbance
This paper addressed the tracking control problem of the robot manipulator with uncertainties and unmatched disturbance by PD control based on adaptive neural network. Adaptive control methods can deal with the control problem of systems with nonlinear and uncertain dynamics, which use measured data...
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| Published in: | IEEE International Conference on Industrial Technology (Online) pp. 1 - 6 |
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| Main Authors: | , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
26.03.2025
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| ISSN: | 2643-2978 |
| Online Access: | Get full text |
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| Abstract | This paper addressed the tracking control problem of the robot manipulator with uncertainties and unmatched disturbance by PD control based on adaptive neural network. Adaptive control methods can deal with the control problem of systems with nonlinear and uncertain dynamics, which use measured data of system trajectory in order to learn and compensate the uncertainties and external disturbances. In this work, a nominal PD control law is used to achieve a sub-optimal performance, and a scheme based on a neural network is implemented to act as a nonlinear compensation whose task is to improve the performance of the nominal controller. A two-degree-of-freedom robot manipulator is proposed to validate the proposed scheme. |
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| AbstractList | This paper addressed the tracking control problem of the robot manipulator with uncertainties and unmatched disturbance by PD control based on adaptive neural network. Adaptive control methods can deal with the control problem of systems with nonlinear and uncertain dynamics, which use measured data of system trajectory in order to learn and compensate the uncertainties and external disturbances. In this work, a nominal PD control law is used to achieve a sub-optimal performance, and a scheme based on a neural network is implemented to act as a nonlinear compensation whose task is to improve the performance of the nominal controller. A two-degree-of-freedom robot manipulator is proposed to validate the proposed scheme. |
| Author | Ren, Ling Wen, Jingdong Peng, Chenchen Qi, Runhua |
| Author_xml | – sequence: 1 givenname: Jingdong surname: Wen fullname: Wen, Jingdong organization: School of Information and Control Engineering, Qingdao University of Technology,Qingdao,China – sequence: 2 givenname: Ling surname: Ren fullname: Ren, Ling email: lingren2687@126.com organization: School of Information and Control Engineering, Qingdao University of Technology,Qingdao,China – sequence: 3 givenname: Chenchen surname: Peng fullname: Peng, Chenchen organization: School of Information and Control Engineering, Qingdao University of Technology,Qingdao,China – sequence: 4 givenname: Runhua surname: Qi fullname: Qi, Runhua organization: School of Information and Control Engineering, Qingdao University of Technology,Qingdao,China |
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| Snippet | This paper addressed the tracking control problem of the robot manipulator with uncertainties and unmatched disturbance by PD control based on adaptive neural... |
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| SubjectTerms | Adaptive control Adaptive Tracking Control Manipulator dynamics Measurement uncertainty Neural networks Nonlinear dynamical systems PD control RBF Neural Network Robot Manipulator Service robots Trajectory Uncertainty |
| Title | Adaptive PD Neural Network Tracking Control for the Uncertain Robot Manipulator with Unmatched Disturbance |
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