École normale supérieure de Cachan

About: École normale supérieure de Cachan is a education organization based out in Cachan, Île-de-France, France. It is known for research contribution in the topics: Decidability & Nonlinear system. The organization has 2717 authors who have published 5585 publications receiving 175925 citations.

Characterization and Prediction of Magnetic Losses in Soft Magnetic Composites Under Distorted Induction Waveform

Abstract: A general approach to magnetic losses in soft magnetic composites (SMC) is discussed. It is applied to exciting conditions typical of applications, where the induction waveform is most frequently nonsinusoidal. The standard predicting approach, based on the statistical theory of losses (STL) and the related concept of loss separation, is extended to the case of granular heterogeneous materials. As a starting point, the classical loss component is calculated, taking into account that in small enough samples the measured loss is independent of the specimen cross-sectional area, because of negligible grain-to-grain (macroscopic) eddy currents. The loss separation is then performed under the conventional sinusoidal induction regime and the STL is used to identify a limited set of parameters, associated with the prediction of the excess loss, by which the energy loss under distorted induction can be predicted. Significant predicting examples are provided, regarding two different SMCs, where the induction waveform is either triangular or distorted by introduction of a third harmonic component.

Tracking control of a vibrating string with an interior mass viewed as delay system

Abstract: A vibrating string, modelled by the wave equation, with an interior mass is considered. It is viewed as a linear delay system. A trajectory tracking problem is solved using a new type of controllability.

Overview of adaptive morphology: Trends and perspectives

Abstract: In this paper we briefly overview emerging trends in ‘Adaptive Morphology’, i.e. work related to the theory and/or applications of image analysis filters, systems, or algorithms based on mathematical morphology, that are adaptive w.r.t. to space or intensity or use any other adaptive scheme. We present a new classification of work in this area structured along several major theoretical perspectives. We then sample specific approaches that develop spatially-variant structuring elements or intensity level-adaptive operators, modeled and implemented either via conventional nonlinear digital filtering or via geometric PDEs. Finally, we discuss some applications.