Reduced-order modelling using nonlinear modes and triple nonlinear modal synthesis

Nonlinear normal modes for damped geometrically nonlinear systems: Application to reduced-order modelling of harmonically forced structures

In order to build efficient reduced-order models (ROMs) for geometrically nonlinear vibrations of thin structures, a normal form procedure is computed for a general class of nonlinear oscillators with quadratic and cubic nonlinearities. The linear perturbation brought by considering a modal viscous damping term is especially addressed in the formulation. A special attention is focused on how al...

On the numerical computation of nonlinear normal modes for reduced-order modelling of conservative vibratory systems

Numerical computation of Nonlinear Normal Modes (NNMs) for conservative vibratory systems is addressed, with the aim of deriving accurate reduced-order models up to large amplitudes. A numerical method is developed, based on the center manifold approach for NNMs, which uses an interpretation of the equations as a transport problem, coupled to a periodicity condition for ensuring manifold’s cont...

Modelling Nonlinear Characteristics using

Real-time control of nonlinear plants requires eecient methods to approximate nonlinear characteristics such as process models or control strategies. Artiicial Neural networks can be applied to represent such characteristics but often this approach does not meet constraints of limited computational resources. Automotive control systems are an example of application areas, where real-time proces...

Reduced Order Modeling of Nonlinear Control Systems

NONLINEAR TIME SERIES MODELLING: ORDER IDENTIFICATION AND WAVELET FILTERING Abbreviated title: Nonlinear time series modelling

In this paper we discuss an approach for modelling nonlinear time series data based on wavelet smoothing. The technique involves decomposing the series into two components a deterministic component which when extracted by wavelet ̄ltering leaves a random component which can be easily modelled using well known linear time series modelling techniques or by a simple diagonal pure bilinear model dis...