Iterative Learning Control for Vibration Suppression of a Robotic Arm
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Iterative Learning Control Systems · Advanced machining processes and optimization · Vibration Control and Rheological Fluids
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical Engineering, National Taiwan University, Taipei 10617, Taiwan
Funding
National Science and Technology Council, Taiwan · Syntec Technology Co., Ltd.
References (25)
Show source-provided references
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