Table of Contents
Advances in Aerospace Engineering
Volume 2015, Article ID 137068, 20 pages
Research Article

Active Vibration Control of the Smart Plate Using Artificial Neural Network Controller

1Department of Electronics & Communication Engineering, Maharshi Dayanand University, Rohtak, Haryana 124001, India
2Department of Mechanical Engineering, University Institute of Engineering &Technology, Maharshi Dayanand University, Rohtak, Haryana 124001, India

Received 5 September 2014; Revised 21 January 2015; Accepted 21 January 2015

Academic Editor: Hamid M. Lankarani

Copyright © 2015 Mohit et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The active vibration control (AVC) of a rectangular plate with single input and single output approach is investigated using artificial neural network. The cantilever plate of finite length, breadth, and thickness having piezoelectric patches as sensors/actuators fixed at the upper and lower surface of the metal plate is considered for examination. The finite element model of the cantilever plate is utilized to formulate the whole strategy. The compact RIO and MATLAB simulation software are exercised to get the appropriate results. The cantilever plate is subjected to impulse input and uniform white noise disturbance. The neural network is trained offline and tuned with LQR controller. The various training algorithms to tune the neural network are exercised. The best efficient algorithm is finally considered to tune the neural network controller designed for active vibration control of the smart plate.