Soft computing-based active vibration control of a flexible structure
Control of vibration of flexible structures has been of remarkable research attention in the last decade. Conventional control methods have not been widely successful due to the dynamic complexity of flexible structures. The literature has recently seen an emergence of demand of soft computing techniques in modelling and control of such dynamic systems. However, the form of soft computing required depends on the nature of the application. This paper accordingly presents investigations into modelling and control techniques based on soft computing methods for vibration suppression of two-dimensional flexible plate structures. The design and analysis of an active vibration control (AVC) system utilising soft computing techniques including neural networks and fuzzy logic is presented. The investigation involves soft computing approach with single-input single-output (SISO) and single-input multi-output (SIMO) AVC structures. A comprehensive comparative assessment of the approaches in terms of performance and design efficiency is also provided. Investigations reveal that the developed soft computing-based AVC system performs very well in the suppression of vibration of a flexible plate structure. It is also shown that the developed SIMO AVC system performs much better in the suppression of vibration of a flexible plate structure in comparison to the SISO AVC system.
active vibration control modelling flexible plate structure neural network fuzzy logic anfis single-input single-output and single input multi-output