Research of Adaptive Vibration Control with Piezoelectric Materials

2010 ◽  
Vol 139-141 ◽  
pp. 2336-2339
Author(s):  
Lei Zhang ◽  
Dong Wei Li ◽  
Zhi Jun Mao
Keyword(s):  
Control System ◽  
Vibration Control ◽  
Piezoelectric Materials ◽  
Active Vibration Control ◽  
Smart Structure ◽  
Cantilever Structure ◽  
Active Vibration ◽  
Adaptive Vibration Control

A kind of adaptive searching optimization active vibration control system of smart structure with piezoelectric materials was put forward, and the smart flexible cantilever structure was analyzed, the active vibration control system was realized in the lab. The result proved the methods’ feasibility and practicability.

On Control of Six Freedom Magnetostrictive Smart Structure

2005 ◽  
Vol 475-479 ◽  
pp. 2111-2114 ◽  
Author(s):  
Jian Qin Mao ◽  
Chao Li ◽  
Hui Bin Xu ◽  
Cheng Bao Jiang ◽  
Lin Li
Keyword(s):  
Control System ◽  
Vibration Control ◽  
Real Time ◽  
Computer Control ◽  
Active Vibration Control ◽  
Smart Structure ◽  
Computer Control System ◽  
Magnetostrictive Actuators ◽  
Active Vibration ◽  
Six Degree Of Freedom

A six degree-of-freedom (DOF) Stewart platform is constructed, which consists of six TbDyFe alloy magnetostrictive actuators, and applied to active vibration control. To control the smart structure, a real time computer control system is built. An improved adaptive filtering algorithm is proposed in this paper, which is used for the computer control system. The results of experiments show that the smart structure and the proposed algorithm are efficient for active vibration control. More than 30 dB of vibration attenuation is achieved in real-time experiments.

Active vibration control of smart structure using poling tuned piezoelectric material

2020 ◽  
Vol 31 (10) ◽  
pp. 1298-1313
Author(s):  
Saurav Sharma ◽  
Anuruddh Kumar ◽  
Rajeev Kumar ◽  
Mohammad Talha ◽  
Rahul Vaish
Keyword(s):  
Fuzzy Logic ◽  
Vibration Control ◽  
Piezoelectric Material ◽  
Fuzzy Logic Controller ◽  
Piezoelectric Materials ◽  
Active Vibration Control ◽  
Time History ◽  
Smart Structure ◽  
Poling Direction ◽  
Active Vibration

In this article, active vibration control of a piezo laminated smart structure is presented using poling tuned piezoelectric material. To improve the performance of existing materials and utilize the actuation potential of different modes of operation ( d31, d33, and d15), simultaneously, the poling direction of the piezoelectric materials is altered and an optimum poling direction is found. Poling tuned piezoelectric patches at the top and bottom layers of the structure are mounted which act as sensors and actuators, respectively. The computational technique used for calculating the time history of the structure is a finite element method. A fuzzy logic controller is developed to compute the appropriate actuator signal as output while taking sensor voltage and its derivative as input. The controlled response due to this fuzzy logic controller is calculated for different piezoelectric materials under consideration and the performance of these materials in active vibration control is compared. Influence of poling angle on the controlled response of the structure is scrutinized and is found to vary from material to material. A large enhancement due to poling tuning is seen in the properties of Pb(Mg1/3Nb2/3)O3-0.35PbTiO3 (PMN-0.35PT), whereas other materials show very less improvement or even decay in the properties.

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.

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