Dong Xu;Guanda Yang;Heyang Feng;Xinnuo Wang;Yupeng Liu
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引用次数: 0
Abstract
With the increasing adoption of robotic manipulators in precision manufacturing and automation, the demand for high efficiency and accuracy has grown significantly. However, these systems often face persistent vibration issues due to their lightweight and flexible structures, which compromise performance. Although there are various studies related to vibration suppression, a comprehensive review of this topic remains absent. This article aims to fill that gap by categorizing recent advances in vibration suppression into passive approaches that use vibration isolators and active approaches that employ closed-loop control systems. Through a critical evaluation of the strengths and limitations of each approach, this review highlights key challenges and emerging trends in the field, offering valuable insights for future research aimed at improving the efficiency and precision of robotic manipulators.
期刊介绍:
The IEEE Open Journal of the Industrial Electronics Society is dedicated to advancing information-intensive, knowledge-based automation, and digitalization, aiming to enhance various industrial and infrastructural ecosystems including energy, mobility, health, and home/building infrastructure. Encompassing a range of techniques leveraging data and information acquisition, analysis, manipulation, and distribution, the journal strives to achieve greater flexibility, efficiency, effectiveness, reliability, and security within digitalized and networked environments.
Our scope provides a platform for discourse and dissemination of the latest developments in numerous research and innovation areas. These include electrical components and systems, smart grids, industrial cyber-physical systems, motion control, robotics and mechatronics, sensors and actuators, factory and building communication and automation, industrial digitalization, flexible and reconfigurable manufacturing, assistant systems, industrial applications of artificial intelligence and data science, as well as the implementation of machine learning, artificial neural networks, and fuzzy logic. Additionally, we explore human factors in digitalized and networked ecosystems. Join us in exploring and shaping the future of industrial electronics and digitalization.