Vibration control of a flexible beam structure using squeeze-mode ER mount

2004 ◽  
Vol 273 (1-2) ◽  
pp. 185-199 ◽  
Author(s):  
W.J. Jung ◽  
W.B. Jeong ◽  
S.R. Hong ◽  
S.-B. Choi
Keyword(s):  
Vibration Control ◽  
Flexible Beam ◽  
Beam Structure

Evolutionary adaptive active vibration control

1997 ◽  
Vol 211 (3) ◽  
pp. 183-193 ◽  
Author(s):  
M A Hossain ◽  
M O Tokhi
Keyword(s):  
Vibration Control ◽  
Control Mechanism ◽  
Vibration Suppression ◽  
Active Vibration Control ◽  
Adaptive Controller ◽  
Recursive Least Squares ◽  
Flexible Beam ◽  
Beam Structure ◽  
Comparative Performance ◽  
Active Vibration

This paper presents an investigation into the development of an adaptive active control mechanism for vibration suppression using genetic algorithms (GAs). GAs are used to estimate the adaptive controller characteristics, where the controller is designed on the basis of optimal vibration suppression using the plant model. This is realized by minimizing the prediction error of the actual plant output and the model output. A MATLAB GA toolbox is used to identify the controller parameters. A comparative performance of the conventional recursive least-squares (RLS) scheme and the GA is presented. The active vibration control system is implemented with both the GA and the RLS schemes, and its performance assessed in the suppression of vibration along a flexible beam structure in each case.

scholarly journals Dynamic Modelling of a Flexible Beam Structure Using Feedforward Neural Networks for Active Vibration Control

2019 ◽  
Vol 16 (1) ◽  
pp. 6263-6280
Author(s):  
Tuan A. Z. Rahman ◽  
A. As’arry ◽  
N. A. Abdul Jalil ◽  
R. Kamil
Keyword(s):  
Neural Networks ◽  
Vibration Control ◽  
Active Vibration Control ◽  
Dynamic Modelling ◽  
Feedforward Neural Networks ◽  
Flexible Beam ◽  
Parametric Modelling ◽  
Beam Structure ◽  
Active Vibration ◽  
Non Parametric

Active vibration control (AVC) techniques show promising results to reduce unwanted vibration level of flexible structures at any desired location. In this paper, the application of non-parametric identification method using feedforward neural networks (FNNs) to model a flexible beam structure for AVC system is presented. An experimental study was carried out to collect input-output dataset of a flexible beam system. The flexible beam was excited using a pseudo-random binary sequence (PRBS) force signal before acquiring the dynamic response of the system. A non-parametric modelling approach of the system was proposed based on feed-forward neural networks (FNNs) while its weight and bias parameters were optimised using chaotic-enhanced stochastic fractal search (SFS) algorithm. The performance of modified SFS algorithm to train a nonlinear auto-regressive exogenous model (NARX) structure FNNs-based model of the system was then compared with its predecessor and with several well-known metaheuristic algorithms. Correlation tests were used to validate the obtained model. Based on the proposed method, a small mean squared error value has been achieved in the validation phase. Considering both convergence rate and result accuracy simultaneously, the chaotic modified SFS algorithm performs significantly better than other training algorithms. In conclusion, the development of a non-parametric model of the flexible beam structure was conducted and validated for future investigations on active vibration control techniques.

Optimized Modeling of Flexible Beam Structure with Pole-Zero Estimation

2019 ◽  
Vol 13 (3) ◽  
pp. 148
Author(s):  
Rickey Pek Eek Ting ◽  
Intan Zaurah Mat Darus ◽  
Shafishuhaza Sahlan ◽  
Mat Hussin Ab Talib
Keyword(s):  
Flexible Beam ◽  
Beam Structure

An Experimental Study of Tendon Vibration Control System for Flexible Space Structures

1991 ◽  
Author(s):  
Yoshisada Murotsu ◽  
Hiroshi Okubo ◽  
Kei Senda
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Vibration Control ◽  
Transfer Functions ◽  
Mimo Systems ◽  
Experimental System ◽  
Space Structures ◽  
Flexible Beam ◽  
Tendon Vibration ◽  
Large Space

Abstract The idea of a tendon vibration control system for a beam-like flexible space structure has been proposed. To verify the feasibility of the concept, an experimental tendon control system has been constructed for the vibration control of a flexible beam simulating Large Space Structures (LSS). This paper discusses modeling, identification, actuator disposition, and controller design for the experimental system. First, a mathematical model of the whole system of the beam and tendon actuator is developed through a finite element method (FEM). Second, to obtain an accurate mathematical model for designing a controller, unknown characteristic parameters are estimated by using an output error method. The validity of the proposed identification scheme is demonstrated by good agreement between the transfer functions of the experimental system and an identified model. Then, disposition of actuators is discussed by using the modal cost analysis. Finally, controllers are designed for SISO and MIMO systems. The feasibility of the proposed controller is verified through numerical simulation and hardware experiments.

scholarly journals Implementation of swarm algorithm in modeling a flexible beam structure

2016 ◽  
Vol 18 (8) ◽  
pp. 4914-4934 ◽  
Author(s):  
Intan Z. Mat Darus ◽  
Rickey Ting Pek Eek ◽  
Shafishuhaza Sahlan ◽  
Pakharuddin Mohd Samin ◽  
Nik M. R Shaharuddin
Keyword(s):  
Flexible Beam ◽  
Beam Structure ◽  
Swarm Algorithm
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