Genetic modeling of a rectangular flexible plate system with free-free-clamped-clamped (FFCC) edges

Hadi, Muhamad Sukri; Hashim, Mohd Hisbany Mohd; Darus, Intan Zaurah Mat

doi:10.1109/ccsii.2012.6470496

Cited by 8 publications

(7 citation statements)

References 4 publications

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“…RLS is a conventional algorithm developed by Gauss in 1821 that can be used to solve the engineering problem by introducing adaptive fitlters. Details of RLS algorithm can be discovered in this article [8]. Meanwhile, ABC algorithm was introduced by Karaboga to solve the numerical optimization problem based on foraging behavior of bee colony.…”

Section: System Identificationmentioning

confidence: 99%

Modelling of Horizontal Flexible Plate Structure Using Artificial Bee Colony Algorithm

Hadi¹,

Darus²

2018

IJET

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This paper presents the performance of system identification for modeling the horizontal flexible plate system using artificial bee colony and recursive least square algorithms. Initially, the experimental rig of flexible plate was designed and fabricated with all edges clamped boundary condition at the horizontal position. Then, the instrumentation and data acquisition systems were integrated into the rig for acquiring the input-output vibration experimentally. The collected data in the experiment will be used later for modeling the dynamic system of horizontal flexible plate system using system identification. The effectiveness of the developed model will be validated using mean squared error, one step ahead prediction, correlation tests and pole zero diagram stability. The estimated of the developed models were found are acceptable and possible to be used as a platform of controller development for vibration suppression of the undesirable vibration in the flexible plate structure. It was found that the artificial bee colony algorithm has performed better in this study by achieving the lowest mean squared error, good correlation test and high stability in the pole zero diagram.

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Section: System Identificationmentioning

confidence: 99%

Modelling of Horizontal Flexible Plate Structure Using Artificial Bee Colony Algorithm

Hadi¹,

Darus²

2018

IJET

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“…The flexible plate structures are widely utilized in a variety of industries including solar panels, electrical bridge decks and circuit board design [3]. This particular structure fulfils most of the desired design  ISSN: 2088-8708 specifications which are low cost, lightweight, lower energy consumption, and capability of being operated at high speed [4].…”

Section: Introductionmentioning

confidence: 99%

“…The thin and lightweight characteristic of flexible plate structure is subjected to higher vibration compared to rigid structures [4]. High vibrations lead to fatigue, noise, structure failure, human discomfort, wear and lessen the efficiency of the flexible plate structure [3]. Therefore, it is critical to eradicate the unpleasant vibration on the flexible plate structure in order to sustain the efficacy of the system.…”

Section: Introductionmentioning

confidence: 99%

Proportional integral derivative controller based on ant colony optimization for vibration cancellation of horizontal flexible plate structure

Zamri

Hadi

Shaari

et al. 2022

IJECE

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<p>Flexible plate structure provides many benefits as compared to their rigid counterparts including lower energy consumption, effective, lightweight, and quick response. However, the vibration easily affects the flexible plate structure resulting in structural damage. This study introduces the modelling of a flexible plate structure based on a system identification technique known as ant colony optimization (ACO) algorithm for vibration control. Firstly, the input-output vibration data that represent the actual structure of flexible plate was achieved from the experiment. Next, the acquired vibration data was used to develop a dynamic model of the flexible plate structure. The performances of the ACO algorithm were assess based on mean squared error (MSE), pole-zero plot and correlation test in order to get a precise and reliable outcome. The results show that ACO algorithm achieved the minimum MSE which was 6.7613×10<sup>−6</sup>, high stability of pole-zero plot and excellent correlation test. Subsequently, the best model of ACO was chosen to create controller based on an active vibration control technique. It was noticed that the controller managed to obtain a 6.19 dB reduction at the first mode vibration in which the percentage of attenuation of the controller was 10.63% for sinusoidal disturbances and 9.64% for multiple sinusoidal disturbances.</p>

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“…Indeed, the active vibration control methods are required to adapt the dynamic response of the system. Thus, it is vital to develop a good model in order to control vibration effectively [1]. The problem of finding a good model for the dynamic of systems often occurred in engineering applications.…”

Section: Introductionmentioning

confidence: 99%

“…Afterward, the validation of the model of the system will be conducted to check whether the model is good enough or not. If the validation is failed, then the whole process should be repeated by obtaining the new set of data [1].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Flexible Beam Using System Identification Approach

2017

ICDET-17, FABMS-17, RIECAE-17, RTET-17, ABMS-17 Feb. 2017

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Abstract-This paper presents the modeling of the flexible beam using system identification method. Due to great attention of flexible structures in most applications, vibration becomes the main problem regarding the dynamic of the structures. In controlling vibration, the system necessarily needs a good model. Therefore, the aim of the work described in this paper is to obtain a dynamic model of the flexible beam. By considering a discrete time form for the system, an autoregressive with exogenous input (ARX) model structures was selected. A square wave signal has been used as an input signal to excite the beam in order to collect input-output data from the experiment. Recursive least square (RLS) estimation algorithm is used to estimate the model parameters based on different model orders. The model validation was done by comparing the measured output against the predicted output in terms of the closeness of both outputs via mean square error (MSE) value. The final result shows the model with the 12th order has the lowest error.

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Genetic modeling of a rectangular flexible plate system with free-free-clamped-clamped (FFCC) edges

Abstract: This paper presents the performance of system identification of a rectangular flexible plate structure using Least

Cited by 8 publications

References 4 publications

Modelling of Horizontal Flexible Plate Structure Using Artificial Bee Colony Algorithm

Modelling of Horizontal Flexible Plate Structure Using Artificial Bee Colony Algorithm

Proportional integral derivative controller based on ant colony optimization for vibration cancellation of horizontal flexible plate structure

Modeling of Flexible Beam Using System Identification Approach

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