Experiments on Fault-Tolerant Active Vibration Control

2008 ◽  
Vol 130 (6) ◽  
Author(s):  
Tao Tao ◽  
Chakradhar Byreddy ◽  
Kenneth D. Frampton
Keyword(s):  
Control System ◽  
Vibration Control ◽  
Filter Design ◽  
Fault Tolerant ◽  
Active Vibration Control ◽  
Research Work ◽  
Sensors And Actuators ◽  
Hybrid Automaton ◽  
Active Vibration ◽  
Detection Filter

The purpose of this work is to experimentally demonstrate a fault-tolerant active vibration control system. Active vibration control is achieved using piezoceramic sensors and actuators (transducers) that are attached to a simply supported beam. These transducers are used by a set of optimal H2 feedback compensators to minimize the lateral vibration of a beam. Actuator faults are detected and isolated with a Beard–Jones fault detection filter. This filter is a special case of Luenberger observer, which produces a residual output with specific directional properties in response to a system fault. In this current research work, a new Beard–Jones filter design methodology is introduced that permits its use on high-order systems and also on systems with feed-through dynamics. The output of this detection filter is monitored by a hybrid automaton that determines when faults occur. This hybrid automaton then directs the selection of a feedback compensator specifically designed for the detected system fault state. The result is a vibration control system that is capable of maintaining optimal performance in the presence of system faults.

Research of active vibration control optimal disposition based on CMQPSO

2021 ◽  
pp. 1-8
Author(s):  
Xiangzhong Meng ◽  
Ying Ma ◽  
Qiang Guo
Keyword(s):  
Particle Swarm Optimization ◽  
Control System ◽  
Vibration Control ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Cloud Model ◽  
Active Vibration Control ◽  
Sensors And Actuators ◽  
Swarm Optimization ◽  
Active Vibration

The adaptive quantum particle swarm optimization algorithm based on cloud model and the multi-island genetic algorithm [15] have obvious advantages in convergence speed to solve the sensor optimization problem, and can effectively achieve global optimization. Due to the installation of sensors and actuators, the electromechanical coupling coefficient of intelligent structures is changed, which affects the vibration energy of structures. In this paper, the reserved energy index of structural vibration control system is taken as the objective optimization function. The position, number, length and control gain of sensors and actuators of active vibration control system are optimized. The adaptive Quantum-behaved Particle Swarm Optimization algorithm in cloud model(CMQPSO) is used as the optimization strategy, and the cantilever beam is taken as an example. This approach is verified its effectiveness and feasibility. It is found that excellent optimization results are obtained.

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.

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
Sign in / Sign up

Export Citation Format

Share Document