DocumentCode
2334743
Title
Direct neuro-AVC modelling and control strategy for vibration suppression of a flexible plate structure
Author
Mat Darus, Intan Z. ; Tokhi, M.O.
Author_Institution
Dept. of Autom. Control & Syst. Eng., Sheffield Univ., UK
Volume
2
fYear
2003
fDate
16-19 Sept. 2003
Firstpage
287
Abstract
This paper investigates the development of a direct neuro-active vibration control (AVC) mechanism for vibration reduction of a flexible plate structure. A multi layer perceptron (MLP) neuro-controller is designed to characterise the ideal controller characteristic using an online adaptation and training mechanism. The effectiveness of the MLP neuro-controller is then verified within the AVC system. The neuro-AVC algorithm thus developed is implemented within a flexible plate simulation environment and its performance in the reduction of deflection at the centre of the plate is assessed. The validation of the algorithm is presented in both the time and frequency domains. Investigations reveal that the developed direct neuro-AVC controller performs very well in the suppression of vibration of a flexible plate structure.
Keywords
backpropagation; flexible structures; multilayer perceptrons; neural net architecture; neurocontrollers; plates (structures); vibration control; algorithm validation; backpropagation-learning algorithm; deflection reduction; direct neuroactive vibration control mechanism; flexible plate structure; multilayer perceptron neurocontroller; online adaptation; training mechanism; vibration suppression; Automatic control; Automatic voltage control; Control systems; Detectors; Finite difference methods; Frequency domain analysis; Modeling; Neural networks; Systems engineering and theory; Vibration control;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Technologies and Factory Automation, 2003. Proceedings. ETFA '03. IEEE Conference
Print_ISBN
0-7803-7937-3
Type
conf
DOI
10.1109/ETFA.2003.1248712
Filename
1248712
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