7 research outputs found

    Nonlinear system-identification of the filling phase of a wet-clutch system

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    The work presented illustrates how the choice of input perturbation signal and experimental design improves the derived model of a nonlinear system, in particular the dynamics of a wet-clutch system. The relationship between the applied input current signal and resulting output pressure in the filling phase of the clutch is established based on bandlimited periodic signals applied at different current operating points and signals approximating the desired filling current signal. A polynomial nonlinear state space model is estimated and validated over a range of measurements and yields better fits over a linear model, while the performance of either model depends on the perturbation signal used for model estimation

    Tensor methods for MIMO decoupling using frequency response

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    Decentralized control design is still commonly applied to design controllers for multivariable systems. The success of decentralized control design methodologies hinges on the quality of decoupling of the system. The aim of this paper is to develop a decoupling procedure that applies to multivariable systems and only requires a frequency response function of the system. The proposed method builds on recent tensor decomposition methods. The potential of the method is shown both in a simulation and using experimental data on an active vibration isolation system

    FREQUENCY DOMAIN BASED FEED FORWARD TUNING FOR FRICTION COMPENSATION

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    ABSTRACT In high precision motion control, performance is often limited by the presence of nonlinearities. In this study, the presence of nonlinear influences in a high precision transmission electron microscope stage is investigated using broadband multisine signals. These measurements yield the nature and level of nonlinearities as well as the best linear approximation of the dynamics. By quantitatively measuring the level of nonlinear influences, this method indicates the relevance of improved modeling. Next, the nonlinear influences are modeled explicitly by measuring the higher order sinusoidal input describing functions (HOSIDF) of the system which describe the 'direct' response of the system at the input frequency as well as at harmonics of the input frequency. Application of this technique yields a structured way to design Coulomb friction feed forward in the presence of nonlinearities. This procedure linearizes the input-output dynamics by applying feed forward and measuring the HOSIDFs which indicate the remaining nonlinear effects. Application of this technique yields a structured way to design feed forward in the presence of nonlinearities. INTRODUCTION When identifying and controlling (mechanical) systems, a linear model structure is often assumed. If nonlinear influences are small, such assumptions may be justified. In order to draw conclusions about nonlinear influences (type and magnitude) the authors in [1, 2, 3] present a multisine based, frequency domain identificatio
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