Neural Networks Based Active Vibration Control of Flexible Linkage Mechanisms

2000 ◽  
Vol 123 (2) ◽  
pp. 266-271 ◽  
Author(s):  
Y. M. Song ◽  
C. Zhang ◽  
Y. Q. Yu
Keyword(s):  
Neural Networks ◽  
Vibration Control ◽  
Inverse Dynamics ◽  
Dynamic Performance ◽  
Active Vibration Control ◽  
Self Tuning ◽  
On Line ◽  
Active Vibration ◽  
Adaptive Control Strategy ◽  
Flexible Linkage

An investigation is presented into the neural networks based active vibration control of flexible linkage mechanisms. A smart mechanism featuring piezoceramic actuators and strain gauge sensors is designed. A nonlinear adaptive control strategy named Neural Networks based Direct Self-Tuning Control (NNBDSC) is employed to suppress the elastodynamic responses of the smart mechanism. To improve the initial robustness of the NNBDSC, the Dynamic Recurrent Neural Network (DRNN) controllers are designed off-line to approximate the inverse dynamics of the smart mechanism. Through on-line control, the strain crest of the flexible link is reduced 60 percent or so and the dynamic performance of the smart mechanism is improved significantly.

Optimal Placement of Piezoelectric Sensors and Actuators for Controlled Flexible Linkage Mechanisms

2005 ◽  
Vol 128 (2) ◽  
pp. 256-260 ◽  
Author(s):  
Xianmin Zhang ◽  
Arthur G. Erdman
Keyword(s):  
Vibration Control ◽  
Simulation Analysis ◽  
Active Vibration Control ◽  
Optimal Placement ◽  
Control Effect ◽  
Sensors And Actuators ◽  
Piezoelectric Sensors And Actuators ◽  
Active Vibration ◽  
Flexible Mechanism ◽  
Flexible Linkage

The optimal placement of sensors and actuators in active vibration control of flexible linkage mechanisms is studied. First, the vibration control model of the flexible mechanism is introduced. Second, based on the concept of the controllability and the observability of the controlled subsystem and the residual subsystem, the optimal model is developed aiming at the maximization of the controllability and the observability of the controlled modes and minimization of those of the residual modes. Finally, a numerical example is presented, which shows that the proposed method is feasible. Simulation analysis shows that to achieve the same control effect, the control system is easier to realize if the sensors and actuators are located in the optimal positions.

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.

Advanced Giant Magnetostrictive Alloys and Application in Actuators for Active Vibration Control

2007 ◽  
Vol 546-549 ◽  
pp. 2143-2150
Author(s):  
Cheng Bao Jiang ◽  
Li Hong Xu ◽  
Tian Li Zhang ◽  
Tian Yu Ma
Keyword(s):  
Vibration Control ◽  
High Performance ◽  
Dynamic Performance ◽  
Active Vibration Control ◽  
Zone Melting ◽  
Improve Performance ◽  
High Electrical Resistivity ◽  
Active Vibration ◽  
Magnetostrictive Actuator ◽  
Giant Magnetostriction

Co and Si were selected as substitutes to improve performance of TbDyFe giant magnetostrictive alloys for special purpose, respectively. The results showed that the Co-doped Tb0.36Dy0.64Fe2 alloys can possess giant magnetostriction over a wide temperature range from -80 to 100 . Optimum magnetostriction, high electrical resistivity and improved corrosion resistance was obtained in Tb0.3Dy0.7(Fe1-xSix)1.95 system. High performance grain-aligned rods with <110> preferred orientation have been successfully prepared by zone melting unidirectional solidification. This paper also presents the design and fabrication of Giant Magnetostrictive Actuator (GMA) for active vibration control with oriented TbDyFe rods. Experimental results showed that the GMA possesses good static and dynamic performance. Excellent damping effect, 20-30 dB under the frequency range from 10 Hz to 120 Hz was obtained.

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