Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Back-propagation learning in expert networks
IEEE Transactions on Neural Networks
Comparison of four neural net learning methods for dynamic system identification
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
ACMOS'08 Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation
Numerical simulation of a flexible plate system for vibration control
WSEAS Transactions on Systems and Control
Control of a flexible plate structure using particle swarm optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Recent Literature Collected by Didier DUBOIS, Henri PRADE and Salvatore SESSA
Fuzzy Sets and Systems
Modeling and simulation of a novel active vibration control system for flexible structures
WSEAS Transactions on Systems and Control
Neural network based prediction schemes of the non-linear seismic response of 3D buildings
Advances in Engineering Software
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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.