Iterative Learning Control for Vibration Suppression of a Robotic Arm
This paper presents a vibration control method for the vibration suppression of a robotic arm. To understand the causes of the vibration in the six-axis manipulator and then eliminate the vibration through an effective control method, the vibration control structure can be divided into two parts. Fi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/2/828 |
| _version_ | 1827629021779722240 |
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| author | Jia-Liang Lin Han-Pang Huang Chun-Yeon Lin |
| author_facet | Jia-Liang Lin Han-Pang Huang Chun-Yeon Lin |
| author_sort | Jia-Liang Lin |
| collection | DOAJ |
| description | This paper presents a vibration control method for the vibration suppression of a robotic arm. To understand the causes of the vibration in the six-axis manipulator and then eliminate the vibration through an effective control method, the vibration control structure can be divided into two parts. First, variational mode decomposition (VMD) and the Hilbert–Huang transform (HHT) algorithm are integrated to analyze the vibration signal and extract the vibration characteristics. Second, a smooth trajectory planning method is used to eliminate the residual vibration. Then, a feedback controller and iterative learning controller are used for controlling the vibration to stabilize the system while compensating for the torque of the elastic-joint model and repetitive errors caused by the vibration through the repeated operation of the arm. In addition, to improve the iterative learning control (ILC) performance, the integration of VMD and the HHT is used to distinguish useless information. The ILC is able to learn more quickly and compensate for the error caused by the vibration. The proposed VMD-HHT iterative learning control for the elastic joint (VH-ILC-EJ) method, along with a laboratory-developed six-axis degree-of-freedom (6-DOF) robotic arm, has been numerically and experimentally validated for vibration suppression. |
| first_indexed | 2024-03-09T13:44:49Z |
| format | Article |
| id | doaj.art-02f0cea774fe4b4fb789934482046752 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T13:44:49Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-02f0cea774fe4b4fb7899344820467522023-11-30T21:02:04ZengMDPI AGApplied Sciences2076-34172023-01-0113282810.3390/app13020828Iterative Learning Control for Vibration Suppression of a Robotic ArmJia-Liang Lin0Han-Pang Huang1Chun-Yeon Lin2Department of Mechanical Engineering, National Taiwan University, Taipei 10617, TaiwanDepartment of Mechanical Engineering, National Taiwan University, Taipei 10617, TaiwanDepartment of Mechanical Engineering, National Taiwan University, Taipei 10617, TaiwanThis paper presents a vibration control method for the vibration suppression of a robotic arm. To understand the causes of the vibration in the six-axis manipulator and then eliminate the vibration through an effective control method, the vibration control structure can be divided into two parts. First, variational mode decomposition (VMD) and the Hilbert–Huang transform (HHT) algorithm are integrated to analyze the vibration signal and extract the vibration characteristics. Second, a smooth trajectory planning method is used to eliminate the residual vibration. Then, a feedback controller and iterative learning controller are used for controlling the vibration to stabilize the system while compensating for the torque of the elastic-joint model and repetitive errors caused by the vibration through the repeated operation of the arm. In addition, to improve the iterative learning control (ILC) performance, the integration of VMD and the HHT is used to distinguish useless information. The ILC is able to learn more quickly and compensate for the error caused by the vibration. The proposed VMD-HHT iterative learning control for the elastic joint (VH-ILC-EJ) method, along with a laboratory-developed six-axis degree-of-freedom (6-DOF) robotic arm, has been numerically and experimentally validated for vibration suppression.https://www.mdpi.com/2076-3417/13/2/828robotic armvibration controlelastic jointiterative learning controlvariational mode decompositionHilbert–Huang transform |
| spellingShingle | Jia-Liang Lin Han-Pang Huang Chun-Yeon Lin Iterative Learning Control for Vibration Suppression of a Robotic Arm Applied Sciences robotic arm vibration control elastic joint iterative learning control variational mode decomposition Hilbert–Huang transform |
| title | Iterative Learning Control for Vibration Suppression of a Robotic Arm |
| title_full | Iterative Learning Control for Vibration Suppression of a Robotic Arm |
| title_fullStr | Iterative Learning Control for Vibration Suppression of a Robotic Arm |
| title_full_unstemmed | Iterative Learning Control for Vibration Suppression of a Robotic Arm |
| title_short | Iterative Learning Control for Vibration Suppression of a Robotic Arm |
| title_sort | iterative learning control for vibration suppression of a robotic arm |
| topic | robotic arm vibration control elastic joint iterative learning control variational mode decomposition Hilbert–Huang transform |
| url | https://www.mdpi.com/2076-3417/13/2/828 |
| work_keys_str_mv | AT jialianglin iterativelearningcontrolforvibrationsuppressionofaroboticarm AT hanpanghuang iterativelearningcontrolforvibrationsuppressionofaroboticarm AT chunyeonlin iterativelearningcontrolforvibrationsuppressionofaroboticarm |