Adaptive neuro fuzzy modelling and vibration control of flexible structure

Abstract

Flexible plate structures have broad applications, ranging from industrial area to space technology. The demand for thin, flexible plate structure has rapidly increased due to industrial evolutions. However, this type of structure leads to high vibration. There are numerous research and study that have been conducted to analyze this problem. The aim of this study is to develop a model characterizing the vibration of a 2-dimensional flexible plate using adaptive neuro-fuzzy inference system (ANFIS). In order to construct the model, sets of data were obtained from numerical analysis. Finite difference method was implemented to discretize the dynamic equation of the plate to finite difference equations. Simulation algorithm was then developed and implemented within the MATLAB environment. The results obtained were validated by comparing the first five frequency parameters with values from other researchers. The sets of data obtained were utilized to develop ARX model and ANFIS model. Then, single-input single-output active vibration controller (SISO-AVC) was devised based on recursive least squares (RLS) algorithm and ANFIS algorithm. The performance of these systems was assessed. The results suggest that ANFIS model is a good tool in system modeling and vibration control. ANFIS-AVC scheme significantly lower the vibration compared to RLS algorithm.