ANFIS Active Vibration Control of Flexible Beam Structures

Volume 1 ◽  
2004 ◽  
Author(s):  
S. Z. Mohd. Hashim ◽  
M. O. Tokhi
Keyword(s):  
Vibration Control ◽  
Fuzzy Inference System ◽  
Dynamic Range ◽  
Vibration Suppression ◽  
Fuzzy Inference ◽  
Least Squares Method ◽  
Active Vibration Control ◽  
Flexible Beam ◽  
Beam Structures ◽  
Inference System

This paper presents the development of an adaptive neuro-fuzzy inference system (ANFIS) controller for vibration control of flexible beam structures. ANFIS constructs a fuzzy inference system (FIS) whose membership function parameters are tuned (adjusted) using the backpropagation algorithm and least squares method. This allows the fuzzy system to learn from the data modeling. To allow the non-linear dynamics of the system be incorporated within the design, a pseudo random binary signal (PRBS) covering the dynamic range of interest of the system is used to train the ANFIS model, which gives good output prediction. Simulation results showing the performance of the developed control scheme in vibration suppression of flexible beam structures, with changes in the excitation signal, are presented and discussed.

scholarly journals Self-Tuning Active Vibration Control in Flexible Beam Structures

1994 ◽  
Vol 208 (4) ◽  
pp. 263-278 ◽  
Author(s):  
M O Tokhi ◽  
M A Hossain
Keyword(s):  
Vibration Control ◽  
Vibration Suppression ◽  
Finite Difference Methods ◽  
Active Vibration Control ◽  
Digital Signal ◽  
Flexible Beam ◽  
Beam Structures ◽  
Single Input Single Output ◽  
Active Vibration ◽  
Single Input

This paper presents the design and performance evaluation of an adaptive active control mechanism for vibration suppression inflexible beam structures. A cantilever beam system in transverse vibration is considered. First-order central finite difference methods are used to study the behaviour of the beam and develop a suitable test and verification platform. An active vibration control algorithm is developed within an adaptive control framework for broadband cancellation of vibration along the beam using a single-input multi-output (SIMO) control structure. The algorithm is implemented on a digital processor incorporating a digital signal processing (DSP) and transputer system. Simulation results verifying the performance of the algorithm in the suppression of vibration along the beam, using single-input single-output and SIMO control structures, are presented and discussed.

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.

A New Method to Identify the Preisach Distribution Function of Hysteresis

2005 ◽  
Vol 475-479 ◽  
pp. 2107-2110 ◽  
Author(s):  
Fan Li ◽  
Jian Qin Mao ◽  
Hai Shan Ding ◽  
Wen Bo Zhang ◽  
Hui Bin Xu ◽  
...  
Keyword(s):  
Distribution Function ◽  
Least Squares ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Least Squares Method ◽  
Input Sequence ◽  
Least Square Method ◽  
Least Square ◽  
New Method ◽  
Inference System

In this paper, a new method which combines the least square method with Tree-Structured fuzzy inference system is presented to approximate the Preisach distribution function. Firstly, by devising the input sequence and measure the output, discrete Preisach measure can be identified by the use of the least squares method. Then, the Preisach function can be obtained with Tree-Structured fuzzy inference system without any special smoothing means. So, this new method is not sensitive to noise, and is a universal approximator of the Preisach function. It collect the merit and overcome the deficiency of the existing methods.

Adaptive active vibration suppression of flexible beam structures

2008 ◽  
Vol 222 (3) ◽  
pp. 357-364 ◽  
Author(s):  
Y Xia ◽  
A Ghasempoor
Keyword(s):  
Vibration Control ◽  
Time Delays ◽  
Vibration Suppression ◽  
Control Strategies ◽  
Linear Optimization ◽  
Active Vibration Control ◽  
Flexible Beam ◽  
Active Vibration Suppression ◽  
Active Vibration ◽  
Suppression System

Vibration control strategies strive to reduce the effect of harmful vibrations on machinery and people. In general, these strategies are classified as passive or active. Although passive vibration control techniques are generally less complex, there is a limit to their effectiveness. Active vibration control strategies, on the other hand, can be very effective but require more complex algorithms and are especially susceptible to time delays. The current paper introduces a novel vibration suppression system using non-linear optimization. The proposed methodology eliminates the need for a feedback loop and the sensitivity to time delays. The system has been evaluated experimentally and the results show the validity of the proposed methodology.

Realization of Active Vibration Control on Piezoelectric Intelligent Flexible Beam

2011 ◽  
Vol 383-390 ◽  
pp. 5580-5585
Author(s):  
Da Fang Wu ◽  
Liang Huang ◽  
Fei Su ◽  
Cheng Xiang Liu ◽  
Hong Yuan Yang ◽  
...  
Keyword(s):  
Vibration Control ◽  
Cantilever Beam ◽  
Control Strategy ◽  
Vibration Mode ◽  
Vibration Suppression ◽  
Active Vibration Control ◽  
Flexible Beam ◽  
Modal Control ◽  
Structural Damping ◽  
Active Vibration

In this paper, the principle and method of active vibration control of a flexible cantilever beam with PZT actuators was studied. A strategy of active control on the first and second order vibration mode of the flexible cantilever beam are determined and implemented by using the independent modal control. Eexperimental results show that the structural damping of the flexible cantilever beam is improved effectively and excellent effect of vibration suppression is achieved with the control strategy.

Aplikasi Peramalan Kebutuhan Beban Listrik Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS)

2017 ◽  
Vol 3 (1) ◽  
pp. 36-48
Author(s):  
Erwan Ahmad Ardiansyah ◽  
Rina Mardiati ◽  
Afaf Fadhil
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Neuro Fuzzy

Prakiraan atau peramalan beban listrik dibutuhkan dalam menentukan jumlah listrik yang dihasilkan. Ini menentukan  agar tidak terjadi beban berlebih yang menyebabkan pemborosan atau kekurangan beban listrik yang mengakibatkan krisis listrik di konsumen. Oleh karena itu di butuhkan prakiraan atau peramalan yang tepat untuk menghasilkan energi listrik. Teknologi softcomputing dapat digunakan  sebagai metode alternatif untuk prediksi beban litrik jangka pendek salah satunya dengan metode  Adaptive Neuro Fuzzy Inference System pada penelitian tugas akhir ini. Data yang di dapat untuk mendukung penelitian ini adalah data dari APD PLN JAWA BARAT yang berisikan laporan data beban puncak bulanan penyulang area gardu induk majalaya dari januari 2011 sampai desember 2014 sebagai data acuan dan data aktual januari-desember 2015. Data kemudian dilatih menggunakan metode ANFIS pada software MATLAB versi b2010. Dari data hasil pelatihan data ANFIS kemudian dilakukan perbandingan dengan data aktual dan data metode regresi meliputi perbandingan anfis-aktual, regresi-aktual dan perbandingan anfis-regresi-aktual. Dari perbandingan disimpulkan bahwa data metode anfis lebih mendekati data aktual dengan rata-rata 1,4%, menunjukan prediksi ANFIS dapat menjadi referensi untuk peramalan beban listrik dimasa depan.

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