Active vibration control system with multiple inputs

1999 ◽  
Vol 105 (5) ◽  
pp. 2552
Author(s):  
Colin F. Ross ◽  
Graham P. Eatwell
Keyword(s):  
Control System ◽  
Vibration Control ◽  
Active Vibration Control ◽  
Active Vibration

scholarly journals Experimental implementation of artificial neural network-based active vibration control & chatter suppression

2021 ◽  
Author(s):  
Yong Xia
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Control System ◽  
Vibration Control ◽  
Control Strategies ◽  
Active Vibration Control ◽  
Chatter Suppression ◽  
Active Vibration ◽  
Artificial Neural

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.

Characteristics of active vibration control system using gyro-stabilizer

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

Simulation of an active vibration control system in a centerless grinding machine using a reduced updated FE model

2009 ◽  
Vol 49 (3-4) ◽  
pp. 239-245 ◽  
Author(s):  
M.H. Fernandes ◽  
I. Garitaonandia ◽  
J. Albizuri ◽  
J.M. Hernández ◽  
D. Barrenetxea
Keyword(s):  
Control System ◽  
Vibration Control ◽  
Active Vibration Control ◽  
Fe Model ◽  
Active Vibration ◽  
Centerless Grinding ◽  
Grinding Machine

scholarly journals Multidimensional System Identification and Active Vibration Control of a Piezoelectric-Based Sting System Used in Wind Tunnel

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yi Yu ◽  
Xing Shen ◽  
Yun Huang
Keyword(s):  
Control System ◽  
System Identification ◽  
Wind Tunnel ◽  
Vibration Control ◽  
Active Vibration Control ◽  
Low Frequency ◽  
Vibration Monitoring ◽  
Multidimensional System ◽  
Monitoring Method ◽  
Active Vibration

In wind tunnel tests, the cantilever sting is usually used to support aircraft models because of its simple structure and low aerodynamic interference. However, in some special conditions, big-amplitude and low-frequency vibration would occur easily on the model not only in the pitch direction but also in the yaw direction, resulting in inaccurate data and even damage of the supporting structure. In this paper, aiming at suppressing the vibration in pitch and yaw plane, a multidimensional system identification and active vibration control system on the basis of piezoelectric actuators is established. A vibration monitoring method based on the strain-displacement transformation (SDT) matrix is proposed, which can transform strain signals into vibration displacements. The system identification based on chirp-Z transform (CZT) is applied to improve the adaptability and precision of the building process for the system model. After that, the hardware platform as well as the software control system based on the classical proportional-derivative (PD) algorithm is built. A series of experiments are carried out, and the results show the exactness of the vibration monitoring method. The system identification process is completed, and the controller is designed. Vibration control experiments verify the effectiveness of the controller, and the results indicate that vibrations in pitch and yaw directions are attenuated apparently. The spectrum power is reduced over 14.8 dB/Hz, which prove that the multidimensional identification and active vibration control system has the capability to decline vibration from different directions.

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