Investigation of active vibration control system for trailed two-wheeled implements

Author(s):  
H-J Kim

This paper presents an active vibration control (AVC) system for trailed two-wheeled implements (TTWI) equipped with high precision electronic devices. With the aim of isolating disturbance forces to the devices, a hydraulically actuated vibration control system is devised. In order to suppress vibratory motions to the body components, considering the TTWI system characteristics, a vibration control and a force tracking control strategy is adopted. As the vibration controller, the adaptive and skyhook control schemes are applied. From full order and reduced order model for the actuating module, as the tracking controller, the sliding mode control scheme is adopted regarding parameter variations. On the basis of the roll plane TTWI system model, simulation work is performed. Finally, after implementation of the experimental setup with the TTWI system and the road simulating module considering practical requirements, actual performance of the devised AVC system is evaluated in various disturbance conditions.

2018 ◽  
Vol 67 (2) ◽  
pp. 020702
Author(s):  
Luo Dong-Yun ◽  
Cheng Bing ◽  
Zhou Yin ◽  
Wu Bin ◽  
Wang Xiao-Long ◽  
...  

2021 ◽  
Author(s):  
Yong Xia

Vibration control strategies strive to reduce the effect of harmful vibrations such as machining chatter. In general, these strategies are classified as passive or active. While passive vibration control techniques are generally less complex, there is a limit to their effectiveness. Active vibration control strategies, which work by providing an additional energy supply to vibration systems, on the other hand, require more complex algorithms but can be very effective. In this work, a novel artificial neural network-based active vibration control system has been developed. The developed system can detect the sinusoidal vibration component with the highest power and suppress it in one control cycle, and in subsequent cycles, sinusoidal signals with the next highest power will be suppressed. With artificial neural networks trained to cover enough frequency and amplitude ranges, most of the original vibration can be suppressed. The efficiency of the proposed methodology has been verified experimentally in the vibration control of a cantilever beam. Artificial neural networks can be trained automatically for updated time delays in the system when necessary. Experimental results show that the developed active vibration control system is real time, adaptable, robust, effective and easy to be implemented. Finally, an experimental setup of chatter suppression for a lathe has been successfully implemented, and the successful techniques used in the previous artificial neural network-based active vibration control system have been utilized for active chatter suppression in turning.


1998 ◽  
Vol 20 (3) ◽  
pp. 176-183 ◽  
Author(s):  
Hiroto Higashiyama ◽  
Masaaki Yamada ◽  
Yukihiko Kazao ◽  
Masao Namiki

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