Modeling flexible plate structure system with free-free-clamped-clamped (FFCC) edges using Particle Swarm Optimization
This paper presents the performance of system identification for rectangular flexible plate using conventional parametric modeling approach by Recursive Least Squares (RLS) and intelligent parametric modeling approach by Particle swarm Optimization (PSO). The experimental rig of rectangular flexible plate with free-free-clamped-clamped edges boundary condition designed and fabricated in this research. The experimental study was conducted to collect the input-output data using a vibration flexible plate complete with data acquisition and instrumentation system. The input-output data will be used during developed the system identification. The whole developed model using RLS and PSO were validated using mean squares error (MSE), one step ahead prediction (OSA) and correlation test. The estimated of developed models was found are comparable, acceptable and possible to be used as a platform of controller development later on. As a comparison between developed system, it was found that the Particle Swarm Optimization algorithm has perform better in term of the lowest mean squares error which is 0.00032719.
Neuro modelling and vibration control of flexible rectangular plate structure
The demand for soft computing techniques in the modeling and control of dynamic system has increased in recent years especially for flexible structures. Flexible plate structures are extensively used in many space applications, however this type of structure leads to high vibration problems. The aim of this investigation is to modelling and control of two dimensional flexible plate structures. This will involve an identification system including least squares, recursive least squares, and neural networks within an active vibration control framework. A thin rectangular plates with all edges clamped is considered. A simulation algorithm characterising the dynamic behaviour of the plate is developed through a discretisation of the governing partial differential equation formulation of the plate dynamics using finite difference methods. The simulation algorithm thus developed and validated forms a suitable test and verification platform in subsequent investigations for development of vibration control techniques for flexible plate structures. The design and analysis of an active vibration control (AVC) system utilizing conventional and soft computing methods with single-input single-output AVC structure is presented to suppressing the vibration of the flexible plate structures. Finally a comparative performance of the algorithm in implementing AVC system using recursive least square (RLS), Multilayer perceptron neural networks (MLP-NN) and Elman Neural networks (ENN) is presented and discussed.
Exponential stabilization of an axially moving string with geometrical nonlinearity by linear boundary feedback
This paper addresses the vibration suppression problem of an axially moving string using boundary control. Taking into account large transverse motion of the string via the second-order component of Lagrangian strain, a nonlinear oscillation equation is derived for the problem by employing the Hamilton's Principle. Direct Lyapunov method is then adopted to demonstrate that a linear boundary control of negative speed feedback ensures the vibration response of the moving string exponentially stable. The main contributions are a new stability condition in terms of controller gain parameter, and a detailed demonstration on the equilibrium condition at the boundary where the control is applied.